forked from omertov/encoder4editing
-
Notifications
You must be signed in to change notification settings - Fork 0
/
blur_w0_10.txt
16901 lines (16901 loc) · 632 KB
/
blur_w0_10.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
{'batch_size': 8,
'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_blur_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': 8,
'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 = 0.7014011144638062
d_fake_loss = 0.6861452460289001
discriminator_loss = 1.3875463008880615
discriminator_r1_loss = 0.13707683980464935
encoder_discriminator_loss = 0.6992362141609192
encoder_discriminator_loss_weighted = 0.06992362141609192
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0294501781463623
id_improve = -1.0294502130709589
id_improve_weighted = -0.5147251065354794
loss_l2 = 0.3084276616573334
loss_l2_weighted = 0.3084276616573334
loss_lpips = 0.7200731039047241
loss_lpips_weighted = 0.5760584831237793
loss_simclr = 2.4458744525909424
loss_simclr_weighted = 24.458744525909424
loss = 25.927879333496094
Metrics for train, step 50
d_real_loss = 0.6061135530471802
d_fake_loss = 0.684654951095581
discriminator_loss = 1.2907685041427612
encoder_discriminator_loss = 0.6377359628677368
encoder_discriminator_loss_weighted = 0.06377359628677369
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9977615475654602
id_improve = -0.9977615182287991
id_improve_weighted = -0.49888075911439955
loss_l2 = 0.27248629927635193
loss_l2_weighted = 0.27248629927635193
loss_lpips = 0.6915221810340881
loss_lpips_weighted = 0.5532177448272705
loss_simclr = 0.6745035648345947
loss_simclr_weighted = 6.745035648345947
loss = 8.133394241333008
Metrics for train, step 100
d_real_loss = 0.49872493743896484
d_fake_loss = 0.6784805059432983
discriminator_loss = 1.1772054433822632
encoder_discriminator_loss = 0.5540891885757446
encoder_discriminator_loss_weighted = 0.055408918857574464
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9952993392944336
id_improve = -0.9952993096085265
id_improve_weighted = -0.49764965480426326
loss_l2 = 0.23256650567054749
loss_l2_weighted = 0.23256650567054749
loss_lpips = 0.687124490737915
loss_lpips_weighted = 0.5496995925903321
loss_simclr = 0.004353084601461887
loss_simclr_weighted = 0.043530846014618874
loss = 1.378855586051941
Metrics for train, step 150
d_real_loss = 0.42425277829170227
d_fake_loss = 0.6667118072509766
discriminator_loss = 1.0909645557403564
encoder_discriminator_loss = 0.49077850580215454
encoder_discriminator_loss_weighted = 0.04907785058021546
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0563395023345947
id_improve = -1.0563395055942237
id_improve_weighted = -0.5281697527971119
loss_l2 = 0.29436323046684265
loss_l2_weighted = 0.29436323046684265
loss_lpips = 0.6852954626083374
loss_lpips_weighted = 0.5482363700866699
loss_simclr = 0.01116945780813694
loss_simclr_weighted = 0.1116945780813694
loss = 1.5315418243408203
Metrics for train, step 200
d_real_loss = 0.3992457389831543
d_fake_loss = 0.6520737409591675
discriminator_loss = 1.0513194799423218
encoder_discriminator_loss = 0.46373167634010315
encoder_discriminator_loss_weighted = 0.046373167634010316
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.989721417427063
id_improve = -0.9897214081138372
id_improve_weighted = -0.4948607040569186
loss_l2 = 0.37305161356925964
loss_l2_weighted = 0.37305161356925964
loss_lpips = 0.6920281648635864
loss_lpips_weighted = 0.5536225318908692
loss_simclr = 0.0007463098736479878
loss_simclr_weighted = 0.007463098736479878
loss = 1.475371241569519
Metrics for train, step 250
d_real_loss = 0.36569344997406006
d_fake_loss = 0.6364423036575317
discriminator_loss = 1.0021357536315918
encoder_discriminator_loss = 0.45095914602279663
encoder_discriminator_loss_weighted = 0.045095914602279664
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9645257592201233
id_improve = -0.9645257454831153
id_improve_weighted = -0.48226287274155766
loss_l2 = 0.33068227767944336
loss_l2_weighted = 0.33068227767944336
loss_lpips = 0.7036904096603394
loss_lpips_weighted = 0.5629523277282715
loss_simclr = 0.0007169213495217264
loss_simclr_weighted = 0.007169213495217264
loss = 1.4281625747680664
Metrics for train, step 300
d_real_loss = 0.33859413862228394
d_fake_loss = 0.6187728047370911
discriminator_loss = 0.957366943359375
encoder_discriminator_loss = 0.44506770372390747
encoder_discriminator_loss_weighted = 0.04450677037239075
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9703547954559326
id_improve = -0.9703547849785537
id_improve_weighted = -0.4851773924892768
loss_l2 = 0.285331666469574
loss_l2_weighted = 0.285331666469574
loss_lpips = 0.6616501212120056
loss_lpips_weighted = 0.5293200969696045
loss_simclr = 0.0015487271593883634
loss_simclr_weighted = 0.015487271593883634
loss = 1.3598233461380005
Metrics for train, step 350
d_real_loss = 0.33160313963890076
d_fake_loss = 0.599254310131073
discriminator_loss = 0.9308574199676514
encoder_discriminator_loss = 0.4423154294490814
encoder_discriminator_loss_weighted = 0.044231542944908143
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.986385703086853
id_improve = -0.9863857086747885
id_improve_weighted = -0.49319285433739424
loss_l2 = 0.3048604130744934
loss_l2_weighted = 0.3048604130744934
loss_lpips = 0.6867570877075195
loss_lpips_weighted = 0.5494056701660156
loss_simclr = 0.0012551085092127323
loss_simclr_weighted = 0.012551085092127323
loss = 1.4042415618896484
Metrics for train, step 400
d_real_loss = 0.31760942935943604
d_fake_loss = 0.5789468884468079
discriminator_loss = 0.8965563178062439
discriminator_r1_loss = 2.008058547973633
encoder_discriminator_loss = 0.44615358114242554
encoder_discriminator_loss_weighted = 0.044615358114242554
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9845637679100037
id_improve = -0.9845637502148747
id_improve_weighted = -0.49228187510743737
loss_l2 = 0.2694399356842041
loss_l2_weighted = 0.2694399356842041
loss_lpips = 0.6707780361175537
loss_lpips_weighted = 0.536622428894043
loss_simclr = 0.0005381729570217431
loss_simclr_weighted = 0.005381729570217431
loss = 1.3483413457870483
Metrics for train, step 450
d_real_loss = 0.37307292222976685
d_fake_loss = 0.5561478137969971
discriminator_loss = 0.9292207360267639
encoder_discriminator_loss = 0.45394033193588257
encoder_discriminator_loss_weighted = 0.04539403319358826
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0043354034423828
id_improve = -1.0043354112422094
id_improve_weighted = -0.5021677056211047
loss_l2 = 0.3043047785758972
loss_l2_weighted = 0.3043047785758972
loss_lpips = 0.6850152611732483
loss_lpips_weighted = 0.5480122089385987
loss_simclr = 0.0015284566907212138
loss_simclr_weighted = 0.015284566907212138
loss = 1.415163278579712
Metrics for train, step 500
d_real_loss = 0.3149178624153137
d_fake_loss = 0.5328549146652222
discriminator_loss = 0.8477727770805359
encoder_discriminator_loss = 0.461772084236145
encoder_discriminator_loss_weighted = 0.0461772084236145
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9727082252502441
id_improve = -0.9727082576137036
id_improve_weighted = -0.4863541288068518
loss_l2 = 0.3317130208015442
loss_l2_weighted = 0.3317130208015442
loss_lpips = 0.6945396661758423
loss_lpips_weighted = 0.5556317329406738
loss_simclr = 0.00014308650861494243
loss_simclr_weighted = 0.0014308650861494243
loss = 1.4213069677352905
Metrics for train, step 550
d_real_loss = 0.3811391592025757
d_fake_loss = 0.506759762763977
discriminator_loss = 0.8878989219665527
encoder_discriminator_loss = 0.4691542088985443
encoder_discriminator_loss_weighted = 0.04691542088985443
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0051032304763794
id_improve = -1.0051032421179116
id_improve_weighted = -0.5025516210589558
loss_l2 = 0.2139890193939209
loss_l2_weighted = 0.2139890193939209
loss_lpips = 0.6718923449516296
loss_lpips_weighted = 0.5375138759613037
loss_simclr = 0.0002874487836379558
loss_simclr_weighted = 0.002874487836379558
loss = 1.3038444519042969
Metrics for train, step 600
d_real_loss = 0.31276947259902954
d_fake_loss = 0.48047935962677
discriminator_loss = 0.7932488322257996
encoder_discriminator_loss = 0.473915696144104
encoder_discriminator_loss_weighted = 0.047391569614410406
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0017282962799072
id_improve = -1.001728368923068
id_improve_weighted = -0.500864184461534
loss_l2 = 0.31448400020599365
loss_l2_weighted = 0.31448400020599365
loss_lpips = 0.6951700448989868
loss_lpips_weighted = 0.5561360359191895
loss_simclr = 7.69795078667812e-05
loss_simclr_weighted = 0.000769795078667812
loss = 1.4196456670761108
Metrics for train, step 650
d_real_loss = 0.351097047328949
d_fake_loss = 0.4535321593284607
discriminator_loss = 0.8046292066574097
encoder_discriminator_loss = 0.4858105182647705
encoder_discriminator_loss_weighted = 0.048581051826477054
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9723272323608398
id_improve = -0.9723271909169853
id_improve_weighted = -0.48616359545849264
loss_l2 = 0.30569106340408325
loss_l2_weighted = 0.30569106340408325
loss_lpips = 0.6906299591064453
loss_lpips_weighted = 0.5525039672851563
loss_simclr = 0.00031365035101771355
loss_simclr_weighted = 0.0031365035101771355
loss = 1.3960763216018677
Metrics for train, step 700
d_real_loss = 0.3404982388019562
d_fake_loss = 0.42688173055648804
discriminator_loss = 0.7673799991607666
encoder_discriminator_loss = 0.4912317991256714
encoder_discriminator_loss_weighted = 0.04912317991256714
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0178414583206177
id_improve = -1.0178414286347106
id_improve_weighted = -0.5089207143173553
loss_l2 = 0.2534031867980957
loss_l2_weighted = 0.2534031867980957
loss_lpips = 0.6860103607177734
loss_lpips_weighted = 0.5488082885742188
loss_simclr = 5.197971040615812e-05
loss_simclr_weighted = 0.0005197971040615812
loss = 1.360775113105774
Metrics for train, step 750
d_real_loss = 0.3019070327281952
d_fake_loss = 0.40269696712493896
discriminator_loss = 0.7046040296554565
encoder_discriminator_loss = 0.5012027025222778
encoder_discriminator_loss_weighted = 0.05012027025222779
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0399144887924194
id_improve = -1.0399145195260644
id_improve_weighted = -0.5199572597630322
loss_l2 = 0.27248841524124146
loss_l2_weighted = 0.27248841524124146
loss_lpips = 0.6709802150726318
loss_lpips_weighted = 0.5367841720581055
loss_simclr = 0.0003944314958062023
loss_simclr_weighted = 0.003944314958062023
loss = 1.3832944631576538
Metrics for train, step 800
d_real_loss = 0.29713839292526245
d_fake_loss = 0.3833067715167999
discriminator_loss = 0.6804451942443848
discriminator_r1_loss = 2.8987350463867188
encoder_discriminator_loss = 0.5195889472961426
encoder_discriminator_loss_weighted = 0.05195889472961426
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.029055118560791
id_improve = -1.0290549616329372
id_improve_weighted = -0.5145274808164686
loss_l2 = 0.28109925985336304
loss_l2_weighted = 0.28109925985336304
loss_lpips = 0.680856466293335
loss_lpips_weighted = 0.544685173034668
loss_simclr = 0.00025350332725793123
loss_simclr_weighted = 0.0025350332725793123
loss = 1.394805908203125
Metrics for train, step 850
d_real_loss = 0.34024226665496826
d_fake_loss = 0.3621193766593933
discriminator_loss = 0.7023616433143616
encoder_discriminator_loss = 0.5267693996429443
encoder_discriminator_loss_weighted = 0.052676939964294435
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9982213973999023
id_improve = -0.9982214896008372
id_improve_weighted = -0.4991107448004186
loss_l2 = 0.23445534706115723
loss_l2_weighted = 0.23445534706115723
loss_lpips = 0.6629982590675354
loss_lpips_weighted = 0.5303986072540283
loss_simclr = 0.0003108703240286559
loss_simclr_weighted = 0.003108703240286559
loss = 1.3197503089904785
Metrics for train, step 900
d_real_loss = 0.3385410010814667
d_fake_loss = 0.34706389904022217
discriminator_loss = 0.6856049299240112
encoder_discriminator_loss = 0.538760781288147
encoder_discriminator_loss_weighted = 0.0538760781288147
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.052139401435852
id_improve = -1.0521394150564447
id_improve_weighted = -0.5260697075282224
loss_l2 = 0.265738844871521
loss_l2_weighted = 0.265738844871521
loss_lpips = 0.6684811115264893
loss_lpips_weighted = 0.5347848892211914
loss_simclr = 0.00046256481437012553
loss_simclr_weighted = 0.004625648143701255
loss = 1.385095238685608
Metrics for train, step 950
d_real_loss = 0.32003268599510193
d_fake_loss = 0.33155199885368347
discriminator_loss = 0.6515846848487854
encoder_discriminator_loss = 0.5518929362297058
encoder_discriminator_loss_weighted = 0.055189293622970585
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0304781198501587
id_improve = -1.0304781096056104
id_improve_weighted = -0.5152390548028052
loss_l2 = 0.25914430618286133
loss_l2_weighted = 0.25914430618286133
loss_lpips = 0.6720674633979797
loss_lpips_weighted = 0.5376539707183838
loss_simclr = 0.00016292974760290235
loss_simclr_weighted = 0.0016292974760290235
loss = 1.3688559532165527
Metrics for train, step 1000
d_real_loss = 0.29104921221733093
d_fake_loss = 0.3185020983219147
discriminator_loss = 0.6095513105392456
encoder_discriminator_loss = 0.560528039932251
encoder_discriminator_loss_weighted = 0.0560528039932251
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9944259524345398
id_improve = -0.9944260148331523
id_improve_weighted = -0.49721300741657615
loss_l2 = 0.23911677300930023
loss_l2_weighted = 0.23911677300930023
loss_lpips = 0.653019905090332
loss_lpips_weighted = 0.5224159240722657
loss_simclr = 9.6679970738478e-05
loss_simclr_weighted = 0.00096679970738478
loss = 1.315765380859375
Metrics for train, step 1050
d_real_loss = 0.3132399916648865
d_fake_loss = 0.3138861060142517
discriminator_loss = 0.6271260976791382
encoder_discriminator_loss = 0.5746095180511475
encoder_discriminator_loss_weighted = 0.05746095180511475
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0569968223571777
id_improve = -1.0569967025658116
id_improve_weighted = -0.5284983512829058
loss_l2 = 0.25149816274642944
loss_l2_weighted = 0.25149816274642944
loss_lpips = 0.6711376905441284
loss_lpips_weighted = 0.5369101524353027
loss_simclr = 0.00016195312491618097
loss_simclr_weighted = 0.0016195312491618097
loss = 1.3759872913360596
Metrics for train, step 1100
d_real_loss = 0.33423343300819397
d_fake_loss = 0.30864572525024414
discriminator_loss = 0.6428791284561157
encoder_discriminator_loss = 0.5860195159912109
encoder_discriminator_loss_weighted = 0.0586019515991211
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0082037448883057
id_improve = -1.0082037888932973
id_improve_weighted = -0.5041018944466487
loss_l2 = 0.301405131816864
loss_l2_weighted = 0.301405131816864
loss_lpips = 0.6844027042388916
loss_lpips_weighted = 0.5475221633911133
loss_simclr = 0.00021311356977093965
loss_simclr_weighted = 0.0021311356977093965
loss = 1.4137622117996216
Metrics for train, step 1150
d_real_loss = 0.3123168349266052
d_fake_loss = 0.30957531929016113
discriminator_loss = 0.6218921542167664
encoder_discriminator_loss = 0.5978397130966187
encoder_discriminator_loss_weighted = 0.05978397130966187
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9707119464874268
id_improve = -0.9707119389204308
id_improve_weighted = -0.4853559694602154
loss_l2 = 0.2609367370605469
loss_l2_weighted = 0.2609367370605469
loss_lpips = 0.6833866834640503
loss_lpips_weighted = 0.5467093467712403
loss_simclr = 0.0002649609523359686
loss_simclr_weighted = 0.002649609523359686
loss = 1.3554357290267944
Metrics for train, step 1200
d_real_loss = 0.29678472876548767
d_fake_loss = 0.31304895877838135
discriminator_loss = 0.6098337173461914
discriminator_r1_loss = 3.9489798545837402
encoder_discriminator_loss = 0.6155052781105042
encoder_discriminator_loss_weighted = 0.061550527811050415
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.064138412475586
id_improve = -1.0641384089831263
id_improve_weighted = -0.5320692044915631
loss_l2 = 0.231011301279068
loss_l2_weighted = 0.231011301279068
loss_lpips = 0.7039653658866882
loss_lpips_weighted = 0.5631722927093507
loss_simclr = 0.00031025291536934674
loss_simclr_weighted = 0.0031025291536934674
loss = 1.3909058570861816
Metrics for train, step 1250
d_real_loss = 0.30807405710220337
d_fake_loss = 0.31288138031959534
discriminator_loss = 0.6209554672241211
encoder_discriminator_loss = 0.6245511174201965
encoder_discriminator_loss_weighted = 0.062455111742019655
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9555050730705261
id_improve = -0.9555050086928532
id_improve_weighted = -0.4777525043464266
loss_l2 = 0.3177214562892914
loss_l2_weighted = 0.3177214562892914
loss_lpips = 0.6705413460731506
loss_lpips_weighted = 0.5364330768585205
loss_simclr = 0.0004921341314911842
loss_simclr_weighted = 0.004921341314911842
loss = 1.399283528327942
Metrics for train, step 1300
d_real_loss = 0.30712059140205383
d_fake_loss = 0.31408798694610596
discriminator_loss = 0.6212085485458374
encoder_discriminator_loss = 0.636539101600647
encoder_discriminator_loss_weighted = 0.0636539101600647
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.992801308631897
id_improve = -0.9928012224845588
id_improve_weighted = -0.4964006112422794
loss_l2 = 0.3031155467033386
loss_l2_weighted = 0.3031155467033386
loss_lpips = 0.6613509654998779
loss_lpips_weighted = 0.5290807723999024
loss_simclr = 0.000495991378556937
loss_simclr_weighted = 0.00495991378556937
loss = 1.3972108364105225
Metrics for train, step 1350
d_real_loss = 0.3048365116119385
d_fake_loss = 0.3155497908592224
discriminator_loss = 0.6203863024711609
encoder_discriminator_loss = 0.6467856764793396
encoder_discriminator_loss_weighted = 0.06467856764793396
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.02512526512146
id_improve = -1.0251252356683835
id_improve_weighted = -0.5125626178341918
loss_l2 = 0.29402923583984375
loss_l2_weighted = 0.29402923583984375
loss_lpips = 0.6888627409934998
loss_lpips_weighted = 0.5510901927947999
loss_simclr = 6.1351980548352e-05
loss_simclr_weighted = 0.00061351980548352
loss = 1.4229742288589478
Metrics for train, step 1400
d_real_loss = 0.35058480501174927
d_fake_loss = 0.31302857398986816
discriminator_loss = 0.6636133790016174
encoder_discriminator_loss = 0.6438149809837341
encoder_discriminator_loss_weighted = 0.06438149809837342
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.93924880027771
id_improve = -0.9392488717567176
id_improve_weighted = -0.4696244358783588
loss_l2 = 0.30892130732536316
loss_l2_weighted = 0.30892130732536316
loss_lpips = 0.6869900226593018
loss_lpips_weighted = 0.5495920181274414
loss_simclr = 0.00027166155632585287
loss_simclr_weighted = 0.0027166155632585287
loss = 1.3952358961105347
Metrics for train, step 1450
d_real_loss = 0.34166353940963745
d_fake_loss = 0.310680091381073
discriminator_loss = 0.6523436307907104
encoder_discriminator_loss = 0.6510600447654724
encoder_discriminator_loss_weighted = 0.06510600447654724
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0249031782150269
id_improve = -1.0249031856656075
id_improve_weighted = -0.5124515928328037
loss_l2 = 0.24790458381175995
loss_l2_weighted = 0.24790458381175995
loss_lpips = 0.6490954160690308
loss_lpips_weighted = 0.5192763328552247
loss_simclr = 0.00012724651605822146
loss_simclr_weighted = 0.0012724651605822146
loss = 1.3460109233856201
Metrics for train, step 1500
d_real_loss = 0.2944023609161377
d_fake_loss = 0.3128785789012909
discriminator_loss = 0.607280969619751
encoder_discriminator_loss = 0.6479376554489136
encoder_discriminator_loss_weighted = 0.06479376554489136
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0004303455352783
id_improve = -1.000430210842751
id_improve_weighted = -0.5002151054213755
loss_l2 = 0.36233004927635193
loss_l2_weighted = 0.36233004927635193
loss_lpips = 0.6732452511787415
loss_lpips_weighted = 0.5385962009429932
loss_simclr = 0.00011284412175882608
loss_simclr_weighted = 0.0011284412175882608
loss = 1.4670636653900146
Metrics for train, step 1550
d_real_loss = 0.3098320960998535
d_fake_loss = 0.31527256965637207
discriminator_loss = 0.6251046657562256
encoder_discriminator_loss = 0.6484494209289551
encoder_discriminator_loss_weighted = 0.06484494209289551
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0130279064178467
id_improve = -1.0130279071163386
id_improve_weighted = -0.5065139535581693
loss_l2 = 0.2559041976928711
loss_l2_weighted = 0.2559041976928711
loss_lpips = 0.6670434474945068
loss_lpips_weighted = 0.5336347579956054
loss_simclr = 0.00021315175399649888
loss_simclr_weighted = 0.002131517539964989
loss = 1.3630293607711792
Metrics for train, step 1600
d_real_loss = 0.3314075469970703
d_fake_loss = 0.31599265336990356
discriminator_loss = 0.6474002003669739
discriminator_r1_loss = 4.153644561767578
encoder_discriminator_loss = 0.6499550938606262
encoder_discriminator_loss_weighted = 0.06499550938606262
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0232999324798584
id_improve = -1.0232999306172132
id_improve_weighted = -0.5116499653086066
loss_l2 = 0.29227977991104126
loss_l2_weighted = 0.29227977991104126
loss_lpips = 0.6537519693374634
loss_lpips_weighted = 0.5230015754699707
loss_simclr = 0.00019765451725106686
loss_simclr_weighted = 0.0019765451725106686
loss = 1.393903374671936
Metrics for train, step 1650
d_real_loss = 0.36149102449417114
d_fake_loss = 0.31176668405532837
discriminator_loss = 0.6732577085494995
encoder_discriminator_loss = 0.6541895866394043
encoder_discriminator_loss_weighted = 0.06541895866394043
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.056266188621521
id_improve = -1.056266178842634
id_improve_weighted = -0.528133089421317
loss_l2 = 0.1904059499502182
loss_l2_weighted = 0.1904059499502182
loss_lpips = 0.663213849067688
loss_lpips_weighted = 0.5305710792541504
loss_simclr = 0.00012066063936799765
loss_simclr_weighted = 0.0012066063936799765
loss = 1.3157358169555664
Metrics for train, step 1700
d_real_loss = 0.31929445266723633
d_fake_loss = 0.3115609288215637
discriminator_loss = 0.6308553814888
encoder_discriminator_loss = 0.659171462059021
encoder_discriminator_loss_weighted = 0.0659171462059021
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0070258378982544
id_improve = -1.0070258610066958
id_improve_weighted = -0.5035129305033479
loss_l2 = 0.2607662081718445
loss_l2_weighted = 0.2607662081718445
loss_lpips = 0.6656289100646973
loss_lpips_weighted = 0.5325031280517578
loss_simclr = 0.00015230607823468745
loss_simclr_weighted = 0.0015230607823468745
loss = 1.3642224073410034
Metrics for train, step 1750
d_real_loss = 0.28924793004989624
d_fake_loss = 0.310333788394928
discriminator_loss = 0.5995817184448242
encoder_discriminator_loss = 0.6684271097183228
encoder_discriminator_loss_weighted = 0.06684271097183228
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9824159741401672
id_improve = -0.9824159918352962
id_improve_weighted = -0.4912079959176481
loss_l2 = 0.25605008006095886
loss_l2_weighted = 0.25605008006095886
loss_lpips = 0.6368108987808228
loss_lpips_weighted = 0.5094487190246583
loss_simclr = 0.00011974311928497627
loss_simclr_weighted = 0.0011974311928497627
loss = 1.3247469663619995
Metrics for train, step 1800
d_real_loss = 0.3232584297657013
d_fake_loss = 0.31270694732666016
discriminator_loss = 0.6359653472900391
encoder_discriminator_loss = 0.674362063407898
encoder_discriminator_loss_weighted = 0.0674362063407898
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9463687539100647
id_improve = -0.9463687520474195
id_improve_weighted = -0.4731843760237098
loss_l2 = 0.2552095353603363
loss_l2_weighted = 0.2552095353603363
loss_lpips = 0.6346215009689331
loss_lpips_weighted = 0.5076972007751465
loss_simclr = 7.060403004288673e-05
loss_simclr_weighted = 0.0007060403004288673
loss = 1.304233431816101
Metrics for train, step 1850
d_real_loss = 0.3089582920074463
d_fake_loss = 0.31007063388824463
discriminator_loss = 0.6190289258956909
encoder_discriminator_loss = 0.6705598831176758
encoder_discriminator_loss_weighted = 0.06705598831176758
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9809017181396484
id_improve = -0.9809017232619226
id_improve_weighted = -0.4904508616309613
loss_l2 = 0.2574751377105713
loss_l2_weighted = 0.2574751377105713
loss_lpips = 0.6530193090438843
loss_lpips_weighted = 0.5224154472351075
loss_simclr = 8.09979101177305e-05
loss_simclr_weighted = 0.000809979101177305
loss = 1.338207483291626
Metrics for train, step 1900
d_real_loss = 0.3186548054218292
d_fake_loss = 0.30726975202560425
discriminator_loss = 0.6259245872497559
encoder_discriminator_loss = 0.6612935066223145
encoder_discriminator_loss_weighted = 0.06612935066223145
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9541501402854919
id_improve = -0.9541501617059112
id_improve_weighted = -0.4770750808529556
loss_l2 = 0.3050605058670044
loss_l2_weighted = 0.3050605058670044
loss_lpips = 0.6741474866867065
loss_lpips_weighted = 0.5393179893493653
loss_simclr = 0.00029705025372095406
loss_simclr_weighted = 0.0029705025372095406
loss = 1.3905534744262695
Metrics for train, step 1950
d_real_loss = 0.34882599115371704
d_fake_loss = 0.30843663215637207
discriminator_loss = 0.6572626233100891
encoder_discriminator_loss = 0.6662880182266235
encoder_discriminator_loss_weighted = 0.06662880182266236
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9552209377288818
id_improve = -0.9552209936082363
id_improve_weighted = -0.47761049680411816
loss_l2 = 0.27973079681396484
loss_l2_weighted = 0.27973079681396484
loss_lpips = 0.6345911026000977
loss_lpips_weighted = 0.5076728820800781
loss_simclr = 0.00010058937914436683
loss_simclr_weighted = 0.0010058937914436683
loss = 1.3326488733291626
Metrics for train, step 2000
d_real_loss = 0.3611835837364197
d_fake_loss = 0.31028029322624207
discriminator_loss = 0.6714638471603394
discriminator_r1_loss = 4.70698356628418
encoder_discriminator_loss = 0.6679524779319763
encoder_discriminator_loss_weighted = 0.06679524779319763
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9957566857337952
id_improve = -0.9957567360252142
id_improve_weighted = -0.4978783680126071
loss_l2 = 0.24127677083015442
loss_l2_weighted = 0.24127677083015442
loss_lpips = 0.6924000978469849
loss_lpips_weighted = 0.5539200782775879
loss_simclr = 5.225598579272628e-05
loss_simclr_weighted = 0.0005225598579272628
loss = 1.3603930473327637
Metrics for train, step 2050
d_real_loss = 0.3162805736064911
d_fake_loss = 0.3135409951210022
discriminator_loss = 0.6298215389251709
encoder_discriminator_loss = 0.675196647644043
encoder_discriminator_loss_weighted = 0.0675196647644043
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0164611339569092
id_improve = -1.0164610970532522
id_improve_weighted = -0.5082305485266261
loss_l2 = 0.2773859202861786
loss_l2_weighted = 0.2773859202861786
loss_lpips = 0.6703822016716003
loss_lpips_weighted = 0.5363057613372803
loss_simclr = 0.0002028646704275161
loss_simclr_weighted = 0.002028646704275161
loss = 1.3914706707000732
Metrics for train, step 2100
d_real_loss = 0.31632569432258606
d_fake_loss = 0.3099744915962219
discriminator_loss = 0.6263002157211304
encoder_discriminator_loss = 0.6749771237373352
encoder_discriminator_loss_weighted = 0.06749771237373352
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.0259358882904053
id_improve = -1.0259359378833324
id_improve_weighted = -0.5129679689416662
loss_l2 = 0.3181439936161041
loss_l2_weighted = 0.3181439936161041
loss_lpips = 0.6869810819625854
loss_lpips_weighted = 0.5495848655700684
loss_simclr = 5.895332287764177e-05
loss_simclr_weighted = 0.0005895332287764177
loss = 1.4487839937210083
Metrics for train, step 2150
d_real_loss = 0.3382924497127533
d_fake_loss = 0.31139901280403137
discriminator_loss = 0.6496914625167847
encoder_discriminator_loss = 0.6854515075683594
encoder_discriminator_loss_weighted = 0.06854515075683594
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 1.033394694328308
id_improve = -1.033394824480638
id_improve_weighted = -0.516697412240319
loss_l2 = 0.28000152111053467
loss_l2_weighted = 0.28000152111053467
loss_lpips = 0.6653674840927124
loss_lpips_weighted = 0.53229398727417
loss_simclr = 0.00012588057143148035
loss_simclr_weighted = 0.0012588057143148035
loss = 1.398796796798706
Metrics for train, step 2200
d_real_loss = 0.2910420596599579
d_fake_loss = 0.3134159445762634
discriminator_loss = 0.6044579744338989
encoder_discriminator_loss = 0.6895033121109009
encoder_discriminator_loss_weighted = 0.0689503312110901
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9779075980186462
id_improve = -0.9779074812540784
id_improve_weighted = -0.4889537406270392
loss_l2 = 0.2753833532333374
loss_l2_weighted = 0.2753833532333374
loss_lpips = 0.6835049390792847
loss_lpips_weighted = 0.5468039512634277
loss_simclr = 0.00011169261415489018
loss_simclr_weighted = 0.0011169261415489018
loss = 1.3812083005905151
Metrics for train, step 2250
d_real_loss = 0.29159605503082275
d_fake_loss = 0.3134163022041321
discriminator_loss = 0.6050123572349548
encoder_discriminator_loss = 0.6873234510421753
encoder_discriminator_loss_weighted = 0.06873234510421754
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9995841979980469
id_improve = -0.9995841262862086
id_improve_weighted = -0.4997920631431043
loss_l2 = 0.271071195602417
loss_l2_weighted = 0.271071195602417
loss_lpips = 0.6986356973648071
loss_lpips_weighted = 0.5589085578918457
loss_simclr = 0.000115026647108607
loss_simclr_weighted = 0.00115026647108607
loss = 1.399654507637024
Metrics for train, step 2300
d_real_loss = 0.3790853023529053
d_fake_loss = 0.31335484981536865
discriminator_loss = 0.6924401521682739
encoder_discriminator_loss = 0.6846839189529419
encoder_discriminator_loss_weighted = 0.06846839189529419
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9989863634109497
id_improve = -0.9989863419905305
id_improve_weighted = -0.49949317099526525
loss_l2 = 0.2238306999206543
loss_l2_weighted = 0.2238306999206543
loss_lpips = 0.6599834561347961
loss_lpips_weighted = 0.5279867649078369
loss_simclr = 5.981048525427468e-05
loss_simclr_weighted = 0.0005981048525427468
loss = 1.3203771114349365
Metrics for train, step 2350
d_real_loss = 0.25281578302383423
d_fake_loss = 0.31180983781814575
discriminator_loss = 0.56462562084198
encoder_discriminator_loss = 0.6801202297210693
encoder_discriminator_loss_weighted = 0.06801202297210694
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9712005853652954
id_improve = -0.9712005858309567
id_improve_weighted = -0.48560029291547835
loss_l2 = 0.24380645155906677
loss_l2_weighted = 0.24380645155906677
loss_lpips = 0.6728438138961792
loss_lpips_weighted = 0.5382750511169434
loss_simclr = 3.940408714697696e-05
loss_simclr_weighted = 0.0003940408714697696
loss = 1.3360878229141235
Metrics for train, step 2400
d_real_loss = 0.33212733268737793
d_fake_loss = 0.30848804116249084
discriminator_loss = 0.6406153440475464
discriminator_r1_loss = 4.04965877532959
encoder_discriminator_loss = 0.6788997054100037
encoder_discriminator_loss_weighted = 0.06788997054100036
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9706640839576721
id_improve = -0.9706641326192766
id_improve_weighted = -0.4853320663096383
loss_l2 = 0.2722632586956024
loss_l2_weighted = 0.2722632586956024
loss_lpips = 0.6968185901641846
loss_lpips_weighted = 0.5574548721313477
loss_simclr = 6.321560795186087e-05
loss_simclr_weighted = 0.0006321560795186087
loss = 1.3835722208023071
Metrics for train, step 2450
d_real_loss = 0.36827999353408813
d_fake_loss = 0.30971866846084595
discriminator_loss = 0.6779986619949341
encoder_discriminator_loss = 0.6858680248260498
encoder_discriminator_loss_weighted = 0.06858680248260499
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9885886907577515
id_improve = -0.9885886977426708
id_improve_weighted = -0.4942943488713354
loss_l2 = 0.35409626364707947
loss_l2_weighted = 0.35409626364707947
loss_lpips = 0.7070083618164062
loss_lpips_weighted = 0.565606689453125
loss_simclr = 7.866240775911137e-05
loss_simclr_weighted = 0.0007866240775911137
loss = 1.4833707809448242
Metrics for train, step 2500
d_real_loss = 0.36834603548049927
d_fake_loss = 0.31460559368133545
discriminator_loss = 0.6829516291618347
encoder_discriminator_loss = 0.6909645795822144
encoder_discriminator_loss_weighted = 0.06909645795822143
total_delta_loss = 0.0
total_delta_loss_weighted = 0.0
loss_id = 0.9757401347160339
id_improve = -0.9757400813978165
id_improve_weighted = -0.48787004069890827
loss_l2 = 0.26682910323143005
loss_l2_weighted = 0.26682910323143005
loss_lpips = 0.6902505159378052
loss_lpips_weighted = 0.5522004127502441
loss_simclr = 6.442231097025797e-05
loss_simclr_weighted = 0.0006442231097025797
loss = 1.3766403198242188
Metrics for train, step 2550
d_real_loss = 0.3121836185455322
d_fake_loss = 0.31501132249832153
discriminator_loss = 0.6271949410438538
encoder_discriminator_loss = 0.6958665251731873
encoder_discriminator_loss_weighted = 0.06958665251731873