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color_w0_10.txt
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color_w0_10.txt
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{'batch_size': 9,
'board_interval': 50,
'checkpoint_path': None,
'd_reg_every': 16,
'dataset_type': 'ffhq_encode',
'delta_norm': 2,
'delta_norm_lambda': 0.0002,
'encoder_type': 'Encoder4Editing',
'exp_dir': 'experiment/ffhq_color_w0_10',
'id_lambda': 0.5,
'image_interval': 100,
'keep_optimizer': False,
'l2_lambda': 1.0,
'learning_rate': 0.0001,
'lpips_lambda': 0.8,
'lpips_type': 'alex',
'max_steps': 40000,
'n_views': 2,
'optim_name': 'ranger',
'progressive_start': 20000,
'progressive_step_every': 2000,
'progressive_steps': [0,
20000,
22000,
24000,
26000,
28000,
30000,
32000,
34000,
36000,
38000,
40000,
42000,
44000],
'r1': 10,
'resume_training_from_ckpt': None,
'save_interval': 20000,
'save_training_data': False,
'simclr_lambda': 10.0,
'simclr_temperature': 0.07,
'start_from_latent_avg': True,
'stylegan_size': 256,
'stylegan_weights': 'pretrained_models/stylegan2-ffhq-config-f.pt',
'sub_exp_dir': None,
'test_batch_size': 9,
'test_workers': 4,
'train_decoder': False,
'update_param_list': None,
'use_w_pool': True,
'val_interval': 10000,
'w_discriminator_lambda': 0.1,
'w_discriminator_lr': 2e-05,
'w_pool_size': 50,
'workers': 8}
Loading encoders weights from irse50!
Loading decoder weights from pretrained!
weights pretrained_models/stylegan2-ffhq-config-f.pt
stylegan weights pretrained_models/stylegan2-ffhq-config-f.pt
Loading ResNet ArcFace
Loading dataset for ffhq_encode
dataset {'transforms': <class 'configs.transforms_config.EncodeTransforms'>, 'train_source_root': '/data/shpx/notebooks/opoursaeed/dev/encoder4editing/images1024', 'train_target_root': '/data/shpx/notebooks/opoursaeed/dev/encoder4editing/images1024', 'test_source_root': '/data/shpx/notebooks/opoursaeed/dev/encoder4editing/celeba', 'test_target_root': '/data/shpx/notebooks/opoursaeed/dev/encoder4editing/celeba'}
dir /data/shpx/notebooks/opoursaeed/dev/encoder4editing/images1024
dir /data/shpx/notebooks/opoursaeed/dev/encoder4editing/images1024
dir /data/shpx/notebooks/opoursaeed/dev/encoder4editing/celeba
dir /data/shpx/notebooks/opoursaeed/dev/encoder4editing/celeba
Number of training samples: 61089
Number of test samples: 30000
Changed progressive stage to: ProgressiveStage.WTraining
Metrics for train, step 0
d_real_loss = 0.7012137174606323
d_fake_loss = 0.6861597299575806
discriminator_loss = 1.387373447418213
discriminator_r1_loss = 0.1361595094203949
encoder_discriminator_loss = 0.6991804242134094
encoder_discriminator_loss_weighted = 0.06991804242134095
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0385810136795044
id_improve = -1.0385809666994545
id_improve_weighted = -0.5192904833497273
loss_l2 = 0.2973771393299103
loss_l2_weighted = 0.2973771393299103
loss_lpips = 0.7068859338760376
loss_lpips_weighted = 0.5655087471008301
loss_simclr = 2.6273999214172363
loss_simclr_weighted = 26.273999214172363
loss = 27.726093292236328
Metrics for train, step 50
d_real_loss = 0.5987836718559265
d_fake_loss = 0.6847481727600098
discriminator_loss = 1.283531904220581
encoder_discriminator_loss = 0.6355209350585938
encoder_discriminator_loss_weighted = 0.06355209350585937
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0080746412277222
id_improve = -1.008074616599414
id_improve_weighted = -0.504037308299707
loss_l2 = 0.2887767255306244
loss_l2_weighted = 0.2887767255306244
loss_lpips = 0.6851978898048401
loss_lpips_weighted = 0.5481583118438721
loss_simclr = 1.2085380554199219
loss_simclr_weighted = 12.085380554199219
loss = 13.48990535736084
Metrics for train, step 100
d_real_loss = 0.48892614245414734
d_fake_loss = 0.6784443259239197
discriminator_loss = 1.1673704385757446
encoder_discriminator_loss = 0.5500677824020386
encoder_discriminator_loss_weighted = 0.05500677824020386
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9990124106407166
id_improve = -0.9990124630017413
id_improve_weighted = -0.49950623150087065
loss_l2 = 0.2586927115917206
loss_l2_weighted = 0.2586927115917206
loss_lpips = 0.6572930812835693
loss_lpips_weighted = 0.5258344650268555
loss_simclr = 0.010510635562241077
loss_simclr_weighted = 0.10510635562241077
loss = 1.4441466331481934
Metrics for train, step 150
d_real_loss = 0.44844886660575867
d_fake_loss = 0.6663356423377991
discriminator_loss = 1.1147844791412354
encoder_discriminator_loss = 0.4875682294368744
encoder_discriminator_loss_weighted = 0.04875682294368744
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9058946967124939
id_improve = -0.9058946373148097
id_improve_weighted = -0.45294731865740484
loss_l2 = 0.2564912438392639
loss_l2_weighted = 0.2564912438392639
loss_lpips = 0.6849639415740967
loss_lpips_weighted = 0.5479711532592774
loss_simclr = 0.007744466885924339
loss_simclr_weighted = 0.07744466885924339
loss = 1.3836113214492798
Metrics for train, step 200
d_real_loss = 0.37305423617362976
d_fake_loss = 0.651443362236023
discriminator_loss = 1.024497628211975
encoder_discriminator_loss = 0.460759699344635
encoder_discriminator_loss_weighted = 0.0460759699344635
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.013157606124878
id_improve = -1.0131576274418168
id_improve_weighted = -0.5065788137209084
loss_l2 = 0.28472399711608887
loss_l2_weighted = 0.28472399711608887
loss_lpips = 0.682036280632019
loss_lpips_weighted = 0.5456290245056152
loss_simclr = 0.004038843791931868
loss_simclr_weighted = 0.040388437919318676
loss = 1.4233962297439575
Metrics for train, step 250
d_real_loss = 0.33128777146339417
d_fake_loss = 0.635837197303772
discriminator_loss = 0.9671249389648438
encoder_discriminator_loss = 0.4497552514076233
encoder_discriminator_loss_weighted = 0.044975525140762335
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9562647342681885
id_improve = -0.9562645800825622
id_improve_weighted = -0.4781322900412811
loss_l2 = 0.2749883234500885
loss_l2_weighted = 0.2749883234500885
loss_lpips = 0.6925210952758789
loss_lpips_weighted = 0.5540168762207032
loss_simclr = 0.00886059645563364
loss_simclr_weighted = 0.0886059645563364
loss = 1.4407190084457397
Metrics for train, step 300
d_real_loss = 0.35441532731056213
d_fake_loss = 0.6185568571090698
discriminator_loss = 0.9729721546173096
encoder_discriminator_loss = 0.44510364532470703
encoder_discriminator_loss_weighted = 0.0445103645324707
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9888313412666321
id_improve = -0.9888313183974888
id_improve_weighted = -0.4944156591987444
loss_l2 = 0.2780683636665344
loss_l2_weighted = 0.2780683636665344
loss_lpips = 0.6861646771430969
loss_lpips_weighted = 0.5489317417144776
loss_simclr = 0.0054995776154100895
loss_simclr_weighted = 0.054995776154100895
loss = 1.4209219217300415
Metrics for train, step 350
d_real_loss = 0.32205647230148315
d_fake_loss = 0.5995855331420898
discriminator_loss = 0.921642005443573
encoder_discriminator_loss = 0.44368720054626465
encoder_discriminator_loss_weighted = 0.04436872005462647
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.98373943567276
id_improve = -0.9837394675446881
id_improve_weighted = -0.49186973377234405
loss_l2 = 0.270012229681015
loss_l2_weighted = 0.270012229681015
loss_lpips = 0.6607341766357422
loss_lpips_weighted = 0.5285873413085938
loss_simclr = 0.005363124888390303
loss_simclr_weighted = 0.05363124888390303
loss = 1.3884693384170532
Metrics for train, step 400
d_real_loss = 0.347335547208786
d_fake_loss = 0.5801793932914734
discriminator_loss = 0.927514910697937
discriminator_r1_loss = 2.183093309402466
encoder_discriminator_loss = 0.4468969702720642
encoder_discriminator_loss_weighted = 0.044689697027206425
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0203973054885864
id_improve = -1.0203973017632961
id_improve_weighted = -0.5101986508816481
loss_l2 = 0.27217933535575867
loss_l2_weighted = 0.27217933535575867
loss_lpips = 0.6701509952545166
loss_lpips_weighted = 0.5361207962036133
loss_simclr = 0.0005874323542229831
loss_simclr_weighted = 0.005874323542229831
loss = 1.3690627813339233
Metrics for train, step 450
d_real_loss = 0.3239108622074127
d_fake_loss = 0.559169590473175
discriminator_loss = 0.8830804824829102
encoder_discriminator_loss = 0.4556456208229065
encoder_discriminator_loss_weighted = 0.04556456208229065
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9584748148918152
id_improve = -0.9584747875730196
id_improve_weighted = -0.4792373937865098
loss_l2 = 0.3316970467567444
loss_l2_weighted = 0.3316970467567444
loss_lpips = 0.6816272735595703
loss_lpips_weighted = 0.5453018188476563
loss_simclr = 0.0016184155829250813
loss_simclr_weighted = 0.016184155829250813
loss = 1.4179850816726685
Metrics for train, step 500
d_real_loss = 0.3330211043357849
d_fake_loss = 0.5367659330368042
discriminator_loss = 0.8697870373725891
encoder_discriminator_loss = 0.46130603551864624
encoder_discriminator_loss_weighted = 0.04613060355186463
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9794209003448486
id_improve = -0.9794208465350999
id_improve_weighted = -0.48971042326754993
loss_l2 = 0.25663530826568604
loss_l2_weighted = 0.25663530826568604
loss_lpips = 0.6676728129386902
loss_lpips_weighted = 0.5341382503509522
loss_simclr = 0.003564043203368783
loss_simclr_weighted = 0.03564043203368783
loss = 1.3622550964355469
Metrics for train, step 550
d_real_loss = 0.3527461588382721
d_fake_loss = 0.5117363333702087
discriminator_loss = 0.8644825220108032
encoder_discriminator_loss = 0.4660602807998657
encoder_discriminator_loss_weighted = 0.046606028079986574
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9585703611373901
id_improve = -0.9585704673081636
id_improve_weighted = -0.4792852336540818
loss_l2 = 0.2745005190372467
loss_l2_weighted = 0.2745005190372467
loss_lpips = 0.6665706038475037
loss_lpips_weighted = 0.533256483078003
loss_simclr = 0.002435720292851329
loss_simclr_weighted = 0.02435720292851329
loss = 1.358005404472351
Metrics for train, step 600
d_real_loss = 0.33878999948501587
d_fake_loss = 0.48594406247138977
discriminator_loss = 0.824734091758728
encoder_discriminator_loss = 0.4733315110206604
encoder_discriminator_loss_weighted = 0.04733315110206604
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0059012174606323
id_improve = -1.0059012069056432
id_improve_weighted = -0.5029506034528216
loss_l2 = 0.24004065990447998
loss_l2_weighted = 0.24004065990447998
loss_lpips = 0.6377964615821838
loss_lpips_weighted = 0.5102371692657471
loss_simclr = 0.004106317181140184
loss_simclr_weighted = 0.041063171811401844
loss = 1.3416248559951782
Metrics for train, step 650
d_real_loss = 0.2807634770870209
d_fake_loss = 0.4605104625225067
discriminator_loss = 0.7412739396095276
encoder_discriminator_loss = 0.4820866584777832
encoder_discriminator_loss_weighted = 0.048208665847778324
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0165588855743408
id_improve = -1.0165588497701619
id_improve_weighted = -0.5082794248850809
loss_l2 = 0.29168206453323364
loss_l2_weighted = 0.29168206453323364
loss_lpips = 0.6899497509002686
loss_lpips_weighted = 0.5519598007202149
loss_simclr = 0.0018062053713947535
loss_simclr_weighted = 0.018062053713947535
loss = 1.4181920289993286
Metrics for train, step 700
d_real_loss = 0.3310547471046448
d_fake_loss = 0.43533873558044434
discriminator_loss = 0.7663934826850891
encoder_discriminator_loss = 0.4909730553627014
encoder_discriminator_loss_weighted = 0.04909730553627015
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9594457745552063
id_improve = -0.9594457024294469
id_improve_weighted = -0.47972285121472347
loss_l2 = 0.28575652837753296
loss_l2_weighted = 0.28575652837753296
loss_lpips = 0.6867420077323914
loss_lpips_weighted = 0.5493936061859132
loss_simclr = 0.011813672259449959
loss_simclr_weighted = 0.11813672259449959
loss = 1.4821070432662964
Metrics for train, step 750
d_real_loss = 0.32179102301597595
d_fake_loss = 0.4123586416244507
discriminator_loss = 0.734149694442749
encoder_discriminator_loss = 0.500779926776886
encoder_discriminator_loss_weighted = 0.0500779926776886
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9879404902458191
id_improve = -0.9879404517511526
id_improve_weighted = -0.4939702258755763
loss_l2 = 0.2561858296394348
loss_l2_weighted = 0.2561858296394348
loss_lpips = 0.6623445749282837
loss_lpips_weighted = 0.529875659942627
loss_simclr = 0.01859242096543312
loss_simclr_weighted = 0.1859242096543312
loss = 1.5160340070724487
Metrics for train, step 800
d_real_loss = 0.3345191180706024
d_fake_loss = 0.3918200433254242
discriminator_loss = 0.7263391613960266
discriminator_r1_loss = 3.282808780670166
encoder_discriminator_loss = 0.5146474242210388
encoder_discriminator_loss_weighted = 0.05146474242210389
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9898630976676941
id_improve = -0.9898629582280086
id_improve_weighted = -0.4949314791140043
loss_l2 = 0.23084944486618042
loss_l2_weighted = 0.23084944486618042
loss_lpips = 0.6904776096343994
loss_lpips_weighted = 0.5523820877075195
loss_simclr = 0.007526529487222433
loss_simclr_weighted = 0.07526529487222433
loss = 1.404893159866333
Metrics for train, step 850
d_real_loss = 0.3312005400657654
d_fake_loss = 0.3734073042869568
discriminator_loss = 0.7046078443527222
encoder_discriminator_loss = 0.5304707884788513
encoder_discriminator_loss_weighted = 0.053047078847885135
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9842552542686462
id_improve = -0.9842551433377795
id_improve_weighted = -0.49212757166888976
loss_l2 = 0.23725470900535583
loss_l2_weighted = 0.23725470900535583
loss_lpips = 0.6548832654953003
loss_lpips_weighted = 0.5239066123962403
loss_simclr = 0.00408122967928648
loss_simclr_weighted = 0.0408122967928648
loss = 1.3471484184265137
Metrics for train, step 900
d_real_loss = 0.30740633606910706
d_fake_loss = 0.3574202060699463
discriminator_loss = 0.664826512336731
encoder_discriminator_loss = 0.5425618290901184
encoder_discriminator_loss_weighted = 0.054256182909011845
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0184684991836548
id_improve = -1.0184684844894543
id_improve_weighted = -0.5092342422447271
loss_l2 = 0.302923321723938
loss_l2_weighted = 0.302923321723938
loss_lpips = 0.7046532034873962
loss_lpips_weighted = 0.5637225627899171
loss_simclr = 0.0007203202112577856
loss_simclr_weighted = 0.007203202112577856
loss = 1.4373395442962646
Metrics for train, step 950
d_real_loss = 0.36012110114097595
d_fake_loss = 0.34533455967903137
discriminator_loss = 0.7054556608200073
encoder_discriminator_loss = 0.5571315288543701
encoder_discriminator_loss_weighted = 0.05571315288543702
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0233325958251953
id_improve = -1.0233325842354033
id_improve_weighted = -0.5116662921177016
loss_l2 = 0.275657057762146
loss_l2_weighted = 0.275657057762146
loss_lpips = 0.6703463792800903
loss_lpips_weighted = 0.5362771034240723
loss_simclr = 0.0020968473982065916
loss_simclr_weighted = 0.020968473982065916
loss = 1.4002821445465088
Metrics for train, step 1000
d_real_loss = 0.34295040369033813
d_fake_loss = 0.33386677503585815
discriminator_loss = 0.6768171787261963
encoder_discriminator_loss = 0.567274808883667
encoder_discriminator_loss_weighted = 0.0567274808883667
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9649061560630798
id_improve = -0.9649061523377895
id_improve_weighted = -0.48245307616889477
loss_l2 = 0.28490450978279114
loss_l2_weighted = 0.28490450978279114
loss_lpips = 0.6750097870826721
loss_lpips_weighted = 0.5400078296661377
loss_simclr = 0.00022426925715990365
loss_simclr_weighted = 0.0022426925715990365
loss = 1.3663356304168701
Metrics for train, step 1050
d_real_loss = 0.37108856439590454
d_fake_loss = 0.3261997401714325
discriminator_loss = 0.6972882747650146
encoder_discriminator_loss = 0.5735440850257874
encoder_discriminator_loss_weighted = 0.05735440850257874
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0328727960586548
id_improve = -1.0328728186173572
id_improve_weighted = -0.5164364093086786
loss_l2 = 0.3082241415977478
loss_l2_weighted = 0.3082241415977478
loss_lpips = 0.6564881205558777
loss_lpips_weighted = 0.5251904964447022
loss_simclr = 0.00025839044246822596
loss_simclr_weighted = 0.0025839044246822596
loss = 1.4097893238067627
Metrics for train, step 1100
d_real_loss = 0.33197444677352905
d_fake_loss = 0.31520000100135803
discriminator_loss = 0.6471744775772095
encoder_discriminator_loss = 0.5740314722061157
encoder_discriminator_loss_weighted = 0.05740314722061157
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.001060962677002
id_improve = -1.0010608565062284
id_improve_weighted = -0.5005304282531142
loss_l2 = 0.2457750290632248
loss_l2_weighted = 0.2457750290632248
loss_lpips = 0.6649377942085266
loss_lpips_weighted = 0.5319502353668213
loss_simclr = 0.0006331136100925505
loss_simclr_weighted = 0.006331136100925505
loss = 1.3419899940490723
Metrics for train, step 1150
d_real_loss = 0.28912150859832764
d_fake_loss = 0.31022611260414124
discriminator_loss = 0.5993475914001465
encoder_discriminator_loss = 0.5833199620246887
encoder_discriminator_loss_weighted = 0.05833199620246887
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0171245336532593
id_improve = -1.017124481085274
id_improve_weighted = -0.508562240542637
loss_l2 = 0.2699732184410095
loss_l2_weighted = 0.2699732184410095
loss_lpips = 0.6668550968170166
loss_lpips_weighted = 0.5334840774536133
loss_simclr = 0.0003336296940688044
loss_simclr_weighted = 0.003336296940688044
loss = 1.3736878633499146
Metrics for train, step 1200
d_real_loss = 0.3275168836116791
d_fake_loss = 0.3052540421485901
discriminator_loss = 0.6327708959579468
discriminator_r1_loss = 3.9756979942321777
encoder_discriminator_loss = 0.5866024494171143
encoder_discriminator_loss_weighted = 0.05866024494171143
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9900447130203247
id_improve = -0.9900447473757796
id_improve_weighted = -0.4950223736878898
loss_l2 = 0.29903748631477356
loss_l2_weighted = 0.29903748631477356
loss_lpips = 0.7037474513053894
loss_lpips_weighted = 0.5629979610443115
loss_simclr = 0.0005695130093954504
loss_simclr_weighted = 0.0056951300939545035
loss = 1.4214131832122803
Metrics for train, step 1250
d_real_loss = 0.3061935007572174
d_fake_loss = 0.3025572597980499
discriminator_loss = 0.6087507605552673
encoder_discriminator_loss = 0.5998589992523193
encoder_discriminator_loss_weighted = 0.059985899925231935
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9782797694206238
id_improve = -0.9782797801825736
id_improve_weighted = -0.4891398900912868
loss_l2 = 0.26195427775382996
loss_l2_weighted = 0.26195427775382996
loss_lpips = 0.6614959836006165
loss_lpips_weighted = 0.5291967868804932
loss_simclr = 0.001650694408454001
loss_simclr_weighted = 0.01650694408454001
loss = 1.3567838668823242
Metrics for train, step 1300
d_real_loss = 0.320809006690979
d_fake_loss = 0.308271199464798
discriminator_loss = 0.6290801763534546
encoder_discriminator_loss = 0.6298274993896484
encoder_discriminator_loss_weighted = 0.06298274993896484
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9852569699287415
id_improve = -0.9852568994586667
id_improve_weighted = -0.49262844972933334
loss_l2 = 0.2891674041748047
loss_l2_weighted = 0.2891674041748047
loss_lpips = 0.6659649014472961
loss_lpips_weighted = 0.5327719211578369
loss_simclr = 0.0011879915837198496
loss_simclr_weighted = 0.011879915837198496
loss = 1.3894305229187012
Metrics for train, step 1350
d_real_loss = 0.36661767959594727
d_fake_loss = 0.31090205907821655
discriminator_loss = 0.6775197386741638
encoder_discriminator_loss = 0.639521062374115
encoder_discriminator_loss_weighted = 0.0639521062374115
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0032826662063599
id_improve = -1.0032826413710911
id_improve_weighted = -0.5016413206855456
loss_l2 = 0.2435935139656067
loss_l2_weighted = 0.2435935139656067
loss_lpips = 0.700030505657196
loss_lpips_weighted = 0.5600244045257569
loss_simclr = 0.00037360377609729767
loss_simclr_weighted = 0.0037360377609729767
loss = 1.3729474544525146
Metrics for train, step 1400
d_real_loss = 0.3490385115146637
d_fake_loss = 0.31001222133636475
discriminator_loss = 0.659050703048706
encoder_discriminator_loss = 0.6403743624687195
encoder_discriminator_loss_weighted = 0.06403743624687196
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0057286024093628
id_improve = -1.0057286336604092
id_improve_weighted = -0.5028643168302046
loss_l2 = 0.2003399133682251
loss_l2_weighted = 0.2003399133682251
loss_lpips = 0.6600993275642395
loss_lpips_weighted = 0.5280794620513917
loss_simclr = 0.0010383182670921087
loss_simclr_weighted = 0.010383182670921087
loss = 1.3057042360305786
Metrics for train, step 1450
d_real_loss = 0.3699778914451599
d_fake_loss = 0.3087863028049469
discriminator_loss = 0.6787642240524292
encoder_discriminator_loss = 0.6436837315559387
encoder_discriminator_loss_weighted = 0.06436837315559388
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9633820056915283
id_improve = -0.9633819998966323
id_improve_weighted = -0.48169099994831616
loss_l2 = 0.2922130823135376
loss_l2_weighted = 0.2922130823135376
loss_lpips = 0.6841580867767334
loss_lpips_weighted = 0.5473264694213867
loss_simclr = 0.002901396481320262
loss_simclr_weighted = 0.02901396481320262
loss = 1.414612889289856
Metrics for train, step 1500
d_real_loss = 0.3056126534938812
d_fake_loss = 0.30565324425697327
discriminator_loss = 0.6112658977508545
encoder_discriminator_loss = 0.6342136859893799
encoder_discriminator_loss_weighted = 0.06342136859893799
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9377630949020386
id_improve = -0.9377630955229203
id_improve_weighted = -0.4688815477614601
loss_l2 = 0.24811865389347076
loss_l2_weighted = 0.24811865389347076
loss_lpips = 0.6894382834434509
loss_lpips_weighted = 0.5515506267547607
loss_simclr = 0.004945859778672457
loss_simclr_weighted = 0.04945859778672457
loss = 1.381430745124817
Metrics for train, step 1550
d_real_loss = 0.3181568384170532
d_fake_loss = 0.3071902394294739
discriminator_loss = 0.6253470778465271
encoder_discriminator_loss = 0.6387791037559509
encoder_discriminator_loss_weighted = 0.06387791037559509
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0159564018249512
id_improve = -1.0159562266328268
id_improve_weighted = -0.5079781133164134
loss_l2 = 0.3215250074863434
loss_l2_weighted = 0.3215250074863434
loss_lpips = 0.6731616258621216
loss_lpips_weighted = 0.5385293006896973
loss_simclr = 0.0007277007098309696
loss_simclr_weighted = 0.007277007098309696
loss = 1.4391875267028809
Metrics for train, step 1600
d_real_loss = 0.33315935730934143
d_fake_loss = 0.30915477871894836
discriminator_loss = 0.6423141360282898
discriminator_r1_loss = 4.161351680755615
encoder_discriminator_loss = 0.6391870975494385
encoder_discriminator_loss_weighted = 0.06391870975494385
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0030041933059692
id_improve = -1.0030042461326554
id_improve_weighted = -0.5015021230663277
loss_l2 = 0.2285391390323639
loss_l2_weighted = 0.2285391390323639
loss_lpips = 0.6557559370994568
loss_lpips_weighted = 0.5246047496795655
loss_simclr = 0.0019132146844640374
loss_simclr_weighted = 0.019132146844640374
loss = 1.3376967906951904
Metrics for train, step 1650
d_real_loss = 0.34728994965553284
d_fake_loss = 0.3091893792152405
discriminator_loss = 0.6564793586730957
encoder_discriminator_loss = 0.6516628265380859
encoder_discriminator_loss_weighted = 0.0651662826538086
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0441792011260986
id_improve = -1.0441791822926865
id_improve_weighted = -0.5220895911463432
loss_l2 = 0.3064924478530884
loss_l2_weighted = 0.3064924478530884
loss_lpips = 0.7059330344200134
loss_lpips_weighted = 0.5647464275360108
loss_simclr = 0.0006957293371669948
loss_simclr_weighted = 0.006957293371669948
loss = 1.4654520750045776
Metrics for train, step 1700
d_real_loss = 0.3257231116294861
d_fake_loss = 0.30620139837265015
discriminator_loss = 0.6319245100021362
encoder_discriminator_loss = 0.6558093428611755
encoder_discriminator_loss_weighted = 0.06558093428611755
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9947314858436584
id_improve = -0.9947315065397156
id_improve_weighted = -0.4973657532698578
loss_l2 = 0.28242412209510803
loss_l2_weighted = 0.28242412209510803
loss_lpips = 0.6781212687492371
loss_lpips_weighted = 0.5424970149993896
loss_simclr = 0.0002316792233614251
loss_simclr_weighted = 0.002316792233614251
loss = 1.3901846408843994
Metrics for train, step 1750
d_real_loss = 0.32980939745903015
d_fake_loss = 0.305109441280365
discriminator_loss = 0.6349188089370728
encoder_discriminator_loss = 0.6588291525840759
encoder_discriminator_loss_weighted = 0.0658829152584076
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0258064270019531
id_improve = -1.0258063844715555
id_improve_weighted = -0.5129031922357777
loss_l2 = 0.28434449434280396
loss_l2_weighted = 0.28434449434280396
loss_lpips = 0.6926533579826355
loss_lpips_weighted = 0.5541226863861084
loss_simclr = 0.00026435754261910915
loss_simclr_weighted = 0.0026435754261910915
loss = 1.4198968410491943
Metrics for train, step 1800
d_real_loss = 0.32236340641975403
d_fake_loss = 0.3035125136375427
discriminator_loss = 0.6258759498596191
encoder_discriminator_loss = 0.6640990376472473
encoder_discriminator_loss_weighted = 0.06640990376472473
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9308178424835205
id_improve = -0.9308178530385097
id_improve_weighted = -0.46540892651925486
loss_l2 = 0.2769181430339813
loss_l2_weighted = 0.2769181430339813
loss_lpips = 0.6739132404327393
loss_lpips_weighted = 0.5391305923461914
loss_simclr = 0.0001964196126209572
loss_simclr_weighted = 0.001964196126209572
loss = 1.3498317003250122
Metrics for train, step 1850
d_real_loss = 0.3327734172344208
d_fake_loss = 0.3049893379211426
discriminator_loss = 0.6377627849578857
encoder_discriminator_loss = 0.6685303449630737
encoder_discriminator_loss_weighted = 0.06685303449630738
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.999701738357544
id_improve = -0.9997016746136878
id_improve_weighted = -0.4998508373068439
loss_l2 = 0.26837679743766785
loss_l2_weighted = 0.26837679743766785
loss_lpips = 0.6726607084274292
loss_lpips_weighted = 0.5381285667419434
loss_simclr = 0.0004709696222562343
loss_simclr_weighted = 0.004709696222562343
loss = 1.3779189586639404
Metrics for train, step 1900
d_real_loss = 0.3509219288825989
d_fake_loss = 0.30727750062942505
discriminator_loss = 0.6581994295120239
encoder_discriminator_loss = 0.6626558303833008
encoder_discriminator_loss_weighted = 0.06626558303833008
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9430298209190369
id_improve = -0.9430298728661405
id_improve_weighted = -0.47151493643307024
loss_l2 = 0.265226274728775
loss_l2_weighted = 0.265226274728775
loss_lpips = 0.6953816413879395
loss_lpips_weighted = 0.5563053131103516
loss_simclr = 0.0008979699341580272
loss_simclr_weighted = 0.008979699341580272
loss = 1.3682917356491089
Metrics for train, step 1950
d_real_loss = 0.32796865701675415
d_fake_loss = 0.3088890314102173
discriminator_loss = 0.6368576884269714
encoder_discriminator_loss = 0.6648494005203247
encoder_discriminator_loss_weighted = 0.06648494005203247
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9982070922851562
id_improve = -0.9982071661700805
id_improve_weighted = -0.49910358308504027
loss_l2 = 0.25756001472473145
loss_l2_weighted = 0.25756001472473145
loss_lpips = 0.6511417031288147
loss_lpips_weighted = 0.5209133625030518
loss_simclr = 0.000810314086265862
loss_simclr_weighted = 0.00810314086265862
loss = 1.3521649837493896
Metrics for train, step 2000
d_real_loss = 0.30038148164749146
d_fake_loss = 0.31273719668388367
discriminator_loss = 0.6131186485290527
discriminator_r1_loss = 4.111809730529785
encoder_discriminator_loss = 0.6703861951828003
encoder_discriminator_loss_weighted = 0.06703861951828004
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9940553307533264
id_improve = -0.9940552862050632
id_improve_weighted = -0.4970276431025316
loss_l2 = 0.2636878490447998
loss_l2_weighted = 0.2636878490447998
loss_lpips = 0.693403959274292
loss_lpips_weighted = 0.5547231674194336
loss_simclr = 0.0005579802091233432
loss_simclr_weighted = 0.005579802091233432
loss = 1.3880571126937866
Metrics for train, step 2050
d_real_loss = 0.3388318419456482
d_fake_loss = 0.31281962990760803
discriminator_loss = 0.6516515016555786
encoder_discriminator_loss = 0.6762568354606628
encoder_discriminator_loss_weighted = 0.06762568354606628
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0272854566574097
id_improve = -1.027285460796621
id_improve_weighted = -0.5136427303983105
loss_l2 = 0.3168695867061615
loss_l2_weighted = 0.3168695867061615
loss_lpips = 0.6742027401924133
loss_lpips_weighted = 0.5393621921539307
loss_simclr = 0.0022768122144043446
loss_simclr_weighted = 0.022768122144043446
loss = 1.4602683782577515
Metrics for train, step 2100
d_real_loss = 0.36450281739234924
d_fake_loss = 0.3139539957046509
discriminator_loss = 0.6784567832946777
encoder_discriminator_loss = 0.6879191398620605
encoder_discriminator_loss_weighted = 0.06879191398620606
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9749147891998291
id_improve = -0.974914780507485
id_improve_weighted = -0.4874573902537425
loss_l2 = 0.31318095326423645
loss_l2_weighted = 0.31318095326423645
loss_lpips = 0.6917869448661804
loss_lpips_weighted = 0.5534295558929444
loss_simclr = 0.0003821223508566618
loss_simclr_weighted = 0.003821223508566618
loss = 1.4266811609268188
Metrics for train, step 2150
d_real_loss = 0.3421080410480499
d_fake_loss = 0.3171984851360321
discriminator_loss = 0.659306526184082
encoder_discriminator_loss = 0.6907181143760681
encoder_discriminator_loss_weighted = 0.06907181143760681
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0231159925460815
id_improve = -1.0231160300059452
id_improve_weighted = -0.5115580150029726
loss_l2 = 0.362792044878006
loss_l2_weighted = 0.362792044878006
loss_lpips = 0.7142881751060486
loss_lpips_weighted = 0.5714305400848388
loss_simclr = 0.0003739075909834355
loss_simclr_weighted = 0.003739075909834355
loss = 1.5185915231704712
Metrics for train, step 2200
d_real_loss = 0.31385746598243713
d_fake_loss = 0.31683167815208435
discriminator_loss = 0.6306891441345215
encoder_discriminator_loss = 0.6928728818893433
encoder_discriminator_loss_weighted = 0.06928728818893433
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.017208456993103
id_improve = -1.0172084276047018
id_improve_weighted = -0.5086042138023509
loss_l2 = 0.3008699417114258
loss_l2_weighted = 0.3008699417114258
loss_lpips = 0.670901894569397
loss_lpips_weighted = 0.5367215156555176
loss_simclr = 0.00022047162929084152
loss_simclr_weighted = 0.002204716292908415
loss = 1.4176876544952393
Metrics for train, step 2250
d_real_loss = 0.32827821373939514
d_fake_loss = 0.31851428747177124
discriminator_loss = 0.6467925310134888
encoder_discriminator_loss = 0.6953024864196777
encoder_discriminator_loss_weighted = 0.06953024864196777
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.000449776649475
id_improve = -1.000449689105153
id_improve_weighted = -0.5002248445525765
loss_l2 = 0.30423179268836975
loss_l2_weighted = 0.30423179268836975
loss_lpips = 0.6972067356109619
loss_lpips_weighted = 0.5577653884887696
loss_simclr = 0.00018970856035593897
loss_simclr_weighted = 0.0018970856035593897
loss = 1.4336495399475098
Metrics for train, step 2300
d_real_loss = 0.3303523659706116
d_fake_loss = 0.3204062879085541
discriminator_loss = 0.6507586240768433
encoder_discriminator_loss = 0.6984274387359619
encoder_discriminator_loss_weighted = 0.0698427438735962
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.002724289894104
id_improve = -1.0027243340801861
id_improve_weighted = -0.5013621670400931
loss_l2 = 0.39268776774406433
loss_l2_weighted = 0.39268776774406433
loss_lpips = 0.685958981513977
loss_lpips_weighted = 0.5487671852111816
loss_simclr = 0.00015962157340254635
loss_simclr_weighted = 0.0015962157340254635
loss = 1.5142561197280884
Metrics for train, step 2350
d_real_loss = 0.24422860145568848
d_fake_loss = 0.32217684388160706
discriminator_loss = 0.5664054155349731
encoder_discriminator_loss = 0.6955727934837341
encoder_discriminator_loss_weighted = 0.06955727934837341
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0269842147827148
id_improve = -1.0269841867395573
id_improve_weighted = -0.5134920933697786
loss_l2 = 0.2986747920513153
loss_l2_weighted = 0.2986747920513153
loss_lpips = 0.6858652234077454
loss_lpips_weighted = 0.5486921787261964
loss_simclr = 0.0009310513269156218
loss_simclr_weighted = 0.009310513269156218
loss = 1.4397268295288086
Metrics for train, step 2400
d_real_loss = 0.3763267695903778
d_fake_loss = 0.3215178847312927
discriminator_loss = 0.6978446245193481
discriminator_r1_loss = 4.369868755340576
encoder_discriminator_loss = 0.6923638582229614
encoder_discriminator_loss_weighted = 0.06923638582229615
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.970610499382019
id_improve = -0.9706105233894454
id_improve_weighted = -0.4853052616947227
loss_l2 = 0.3218095600605011
loss_l2_weighted = 0.3218095600605011
loss_lpips = 0.6906441450119019
loss_lpips_weighted = 0.5525153160095215
loss_simclr = 0.0031953672878444195
loss_simclr_weighted = 0.031953672878444195
loss = 1.4608203172683716
Metrics for train, step 2450
d_real_loss = 0.3020874559879303
d_fake_loss = 0.32057249546051025
discriminator_loss = 0.6226599216461182
encoder_discriminator_loss = 0.6943319439888
encoder_discriminator_loss_weighted = 0.06943319439888
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0393924713134766
id_improve = -1.0393925218635962
id_improve_weighted = -0.5196962609317981
loss_l2 = 0.31183257699012756
loss_l2_weighted = 0.31183257699012756
loss_lpips = 0.6983273029327393
loss_lpips_weighted = 0.5586618423461914
loss_simclr = 0.0004558489308692515
loss_simclr_weighted = 0.004558489308692515
loss = 1.4641822576522827
Metrics for train, step 2500
d_real_loss = 0.33518102765083313
d_fake_loss = 0.3254188597202301
discriminator_loss = 0.6605998873710632
encoder_discriminator_loss = 0.6973046660423279
encoder_discriminator_loss_weighted = 0.0697304666042328
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0134656429290771
id_improve = -1.013465688874324
id_improve_weighted = -0.506732844437162
loss_l2 = 0.36236536502838135
loss_l2_weighted = 0.36236536502838135
loss_lpips = 0.6953043341636658
loss_lpips_weighted = 0.5562434673309327
loss_simclr = 0.0038618631660938263
loss_simclr_weighted = 0.03861863166093826
loss = 1.5336908102035522
Metrics for train, step 2550
d_real_loss = 0.36438480019569397
d_fake_loss = 0.323312908411026
discriminator_loss = 0.68769770860672
encoder_discriminator_loss = 0.701086699962616
encoder_discriminator_loss_weighted = 0.0701086699962616