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Commit 12038f26 authored by Meet Narendra's avatar Meet Narendra 💬
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Merge branch 'DEV_meetdoshi' into 'DEV' 

Dev meetdoshi merged with DEV.

See merge request !1
parents 9dfa23ae 6cece00c
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2022-10-04 00:58:10,979 INFO Started Feature Maps
2022-10-04 00:58:10,979 INFO Running the model cuda_available = False
2022-10-04 00:58:11,236 INFO Started Style Transfer
2022-10-04 00:58:11,267 INFO Running gradient descent with the following parameters
2022-10-04 00:58:11,267 INFO 5000,0.01,1,0.01
2022-10-04 00:58:11,267 INFO Optimizer = Adam (
Parameter Group 0
amsgrad: False
betas: (0.9, 0.999)
capturable: False
eps: 1e-08
foreach: None
lr: 0.01
maximize: False
weight_decay: 0
)
2022-10-04 00:58:12,945 INFO Epoch = 0 Total Loss = 234316.109375 content Loss = 0.0 style Loss = 23431614.0
2022-10-04 00:58:21,698 INFO Epoch = 10 Total Loss = 31606.79296875 content Loss = 7.066261291503906 style Loss = 3159972.75
2022-10-04 00:58:30,200 INFO Epoch = 20 Total Loss = 14400.4931640625 content Loss = 8.921441078186035 style Loss = 1439157.25
2022-10-04 00:58:38,684 INFO Epoch = 30 Total Loss = 8287.0546875 content Loss = 9.76793098449707 style Loss = 827728.6875
2022-10-04 00:58:47,182 INFO Epoch = 40 Total Loss = 5631.27490234375 content Loss = 10.174300193786621 style Loss = 562110.0625
2022-10-04 00:58:55,662 INFO Epoch = 50 Total Loss = 4148.42724609375 content Loss = 10.584795951843262 style Loss = 413784.28125
2022-10-04 00:59:04,142 INFO Epoch = 60 Total Loss = 3199.865234375 content Loss = 10.848982810974121 style Loss = 318901.65625
2022-10-04 00:59:12,663 INFO Epoch = 70 Total Loss = 2549.94775390625 content Loss = 11.06682014465332 style Loss = 253888.078125
2022-10-04 00:59:21,196 INFO Epoch = 80 Total Loss = 2077.34765625 content Loss = 11.190975189208984 style Loss = 206615.671875
2022-10-04 00:59:29,794 INFO Epoch = 90 Total Loss = 1726.1820068359375 content Loss = 11.344461441040039 style Loss = 171483.765625
2022-10-04 00:59:38,388 INFO Epoch = 100 Total Loss = 1463.0743408203125 content Loss = 11.479227066040039 style Loss = 145159.53125
2022-10-04 00:59:46,825 INFO Epoch = 110 Total Loss = 1265.8553466796875 content Loss = 11.590709686279297 style Loss = 125426.46875
2022-10-04 00:59:55,324 INFO Epoch = 120 Total Loss = 1117.9674072265625 content Loss = 11.700607299804688 style Loss = 110626.6953125
2022-10-04 01:00:04,062 INFO Epoch = 130 Total Loss = 1006.498046875 content Loss = 11.79938793182373 style Loss = 99469.8515625
2022-10-04 01:00:12,550 INFO Epoch = 140 Total Loss = 921.6320190429688 content Loss = 11.884160995483398 style Loss = 90974.78125
2022-10-04 01:00:21,124 INFO Epoch = 150 Total Loss = 855.8607788085938 content Loss = 11.96123218536377 style Loss = 84389.953125
2022-10-04 01:00:29,737 INFO Epoch = 160 Total Loss = 803.77099609375 content Loss = 12.029985427856445 style Loss = 79174.1015625
2022-10-04 01:00:38,283 INFO Epoch = 170 Total Loss = 761.369140625 content Loss = 12.091764450073242 style Loss = 74927.734375
2022-10-04 01:00:46,766 INFO Epoch = 180 Total Loss = 725.9055786132812 content Loss = 12.151314735412598 style Loss = 71375.4296875
2022-10-04 01:00:55,193 INFO Epoch = 190 Total Loss = 695.6036376953125 content Loss = 12.206104278564453 style Loss = 68339.75
2022-10-04 01:01:03,741 INFO Epoch = 200 Total Loss = 669.1712646484375 content Loss = 12.256004333496094 style Loss = 65691.5234375
2022-10-04 01:01:12,205 INFO Epoch = 210 Total Loss = 645.7721557617188 content Loss = 12.304346084594727 style Loss = 63346.78515625
2022-10-04 01:01:20,681 INFO Epoch = 220 Total Loss = 624.7929077148438 content Loss = 12.349298477172852 style Loss = 61244.359375
2022-10-04 01:01:29,193 INFO Epoch = 230 Total Loss = 605.7103271484375 content Loss = 12.392176628112793 style Loss = 59331.8203125
2022-10-04 01:01:37,694 INFO Epoch = 240 Total Loss = 588.19384765625 content Loss = 12.43117904663086 style Loss = 57576.265625
2022-10-04 01:01:46,176 INFO Epoch = 250 Total Loss = 572.0764770507812 content Loss = 12.468263626098633 style Loss = 55960.81640625
2022-10-04 01:01:54,671 INFO Epoch = 260 Total Loss = 557.1376342773438 content Loss = 12.503133773803711 style Loss = 54463.453125
2022-10-04 01:02:03,219 INFO Epoch = 270 Total Loss = 543.2896728515625 content Loss = 12.53659439086914 style Loss = 53075.30859375
2022-10-04 01:02:11,789 INFO Epoch = 280 Total Loss = 530.3758544921875 content Loss = 12.57027530670166 style Loss = 51780.56640625
2022-10-04 01:02:20,300 INFO Epoch = 290 Total Loss = 518.26513671875 content Loss = 12.603023529052734 style Loss = 50566.2109375
2022-10-04 01:02:28,774 INFO Epoch = 300 Total Loss = 506.8891296386719 content Loss = 12.633913040161133 style Loss = 49425.5234375
2022-10-04 01:02:37,244 INFO Epoch = 310 Total Loss = 496.1564636230469 content Loss = 12.66421890258789 style Loss = 48349.2265625
2022-10-04 01:02:45,736 INFO Epoch = 320 Total Loss = 486.0169372558594 content Loss = 12.693431854248047 style Loss = 47332.3515625
2022-10-04 01:02:54,243 INFO Epoch = 330 Total Loss = 476.43463134765625 content Loss = 12.722034454345703 style Loss = 46371.2578125
2022-10-04 01:03:02,678 INFO Epoch = 340 Total Loss = 467.36358642578125 content Loss = 12.74763011932373 style Loss = 45461.59765625
2022-10-04 01:03:11,164 INFO Epoch = 350 Total Loss = 458.76177978515625 content Loss = 12.773143768310547 style Loss = 44598.8671875
2022-10-04 01:03:19,637 INFO Epoch = 360 Total Loss = 450.5729675292969 content Loss = 12.797780990600586 style Loss = 43777.51953125
2022-10-04 01:03:28,252 INFO Epoch = 370 Total Loss = 442.7126159667969 content Loss = 12.823134422302246 style Loss = 42988.94921875
2022-10-04 01:03:36,883 INFO Epoch = 380 Total Loss = 435.16656494140625 content Loss = 12.848091125488281 style Loss = 42231.8515625
2022-10-04 01:03:45,472 INFO Epoch = 390 Total Loss = 427.9437255859375 content Loss = 12.872780799865723 style Loss = 41507.09765625
2022-10-04 01:03:54,083 INFO Epoch = 400 Total Loss = 421.0248107910156 content Loss = 12.89657211303711 style Loss = 40812.82421875
2022-10-04 01:04:02,796 INFO Epoch = 410 Total Loss = 414.37200927734375 content Loss = 12.918611526489258 style Loss = 40145.33984375
2022-10-04 01:04:11,530 INFO Epoch = 420 Total Loss = 407.9482727050781 content Loss = 12.93993854522705 style Loss = 39500.8359375
2022-10-04 01:04:20,076 INFO Epoch = 430 Total Loss = 401.7867431640625 content Loss = 12.961529731750488 style Loss = 38882.5234375
2022-10-04 01:04:28,600 INFO Epoch = 440 Total Loss = 395.91265869140625 content Loss = 12.982783317565918 style Loss = 38292.98828125
2022-10-04 01:04:37,111 INFO Epoch = 450 Total Loss = 390.3022766113281 content Loss = 13.003360748291016 style Loss = 37729.890625
2022-10-04 01:04:45,643 INFO Epoch = 460 Total Loss = 384.906494140625 content Loss = 13.023153305053711 style Loss = 37188.33984375
2022-10-04 01:04:54,322 INFO Epoch = 470 Total Loss = 379.6942138671875 content Loss = 13.042801856994629 style Loss = 36665.14453125
2022-10-04 01:05:02,923 INFO Epoch = 480 Total Loss = 374.6649475097656 content Loss = 13.062613487243652 style Loss = 36160.234375
2022-10-04 01:05:11,401 INFO Epoch = 490 Total Loss = 369.804443359375 content Loss = 13.082564353942871 style Loss = 35672.19140625
2022-10-04 01:05:19,889 INFO Epoch = 500 Total Loss = 365.1194763183594 content Loss = 13.101099967956543 style Loss = 35201.8359375
2022-10-04 01:05:28,353 INFO Epoch = 510 Total Loss = 360.5958251953125 content Loss = 13.11732006072998 style Loss = 34747.84765625
2022-10-04 01:05:36,799 INFO Epoch = 520 Total Loss = 356.2113037109375 content Loss = 13.133686065673828 style Loss = 34307.7578125
2022-10-04 01:05:45,275 INFO Epoch = 530 Total Loss = 351.9555969238281 content Loss = 13.149556159973145 style Loss = 33880.6015625
2022-10-04 01:05:53,745 INFO Epoch = 540 Total Loss = 347.8521728515625 content Loss = 13.164706230163574 style Loss = 33468.7421875
2022-10-04 01:06:02,198 INFO Epoch = 550 Total Loss = 343.8878173828125 content Loss = 13.178564071655273 style Loss = 33070.92578125
2022-10-04 01:06:10,637 INFO Epoch = 560 Total Loss = 340.0307312011719 content Loss = 13.192499160766602 style Loss = 32683.82421875
2022-10-04 01:06:19,099 INFO Epoch = 570 Total Loss = 336.2955017089844 content Loss = 13.205334663391113 style Loss = 32309.017578125
2022-10-04 01:06:27,545 INFO Epoch = 580 Total Loss = 332.6847839355469 content Loss = 13.21759033203125 style Loss = 31946.71875
2022-10-04 01:06:36,001 INFO Epoch = 590 Total Loss = 329.1806335449219 content Loss = 13.229888916015625 style Loss = 31595.07421875
2022-10-04 01:06:44,517 INFO Epoch = 600 Total Loss = 325.7560729980469 content Loss = 13.242679595947266 style Loss = 31251.33984375
2022-10-04 01:06:53,062 INFO Epoch = 610 Total Loss = 322.4200439453125 content Loss = 13.256410598754883 style Loss = 30916.361328125
2022-10-04 01:07:01,697 INFO Epoch = 620 Total Loss = 319.18505859375 content Loss = 13.270450592041016 style Loss = 30591.4609375
2022-10-04 01:07:10,169 INFO Epoch = 630 Total Loss = 316.0299987792969 content Loss = 13.284313201904297 style Loss = 30274.56640625
2022-10-04 01:07:18,779 INFO Epoch = 640 Total Loss = 312.9624938964844 content Loss = 13.297652244567871 style Loss = 29966.482421875
2022-10-04 01:07:27,353 INFO Epoch = 650 Total Loss = 309.9873962402344 content Loss = 13.31077766418457 style Loss = 29667.662109375
2022-10-04 01:07:35,889 INFO Epoch = 660 Total Loss = 307.09698486328125 content Loss = 13.323376655578613 style Loss = 29377.361328125
2022-10-04 01:07:44,383 INFO Epoch = 670 Total Loss = 304.2821960449219 content Loss = 13.335968971252441 style Loss = 29094.625
2022-10-04 01:07:52,890 INFO Epoch = 680 Total Loss = 301.52117919921875 content Loss = 13.347564697265625 style Loss = 28817.36328125
2022-10-04 01:08:01,441 INFO Epoch = 690 Total Loss = 298.8135681152344 content Loss = 13.359440803527832 style Loss = 28545.412109375
2022-10-04 01:08:09,971 INFO Epoch = 700 Total Loss = 296.17889404296875 content Loss = 13.370931625366211 style Loss = 28280.794921875
2022-10-04 01:08:18,487 INFO Epoch = 710 Total Loss = 293.61480712890625 content Loss = 13.38138484954834 style Loss = 28023.345703125
2022-10-04 01:08:27,000 INFO Epoch = 720 Total Loss = 291.1148376464844 content Loss = 13.392017364501953 style Loss = 27772.28515625
2022-10-04 01:08:35,502 INFO Epoch = 730 Total Loss = 288.6687927246094 content Loss = 13.402449607849121 style Loss = 27526.6328125
2022-10-04 01:08:43,962 INFO Epoch = 740 Total Loss = 286.2763671875 content Loss = 13.412226676940918 style Loss = 27286.4140625
2022-10-04 01:08:52,431 INFO Epoch = 750 Total Loss = 283.9483947753906 content Loss = 13.422285079956055 style Loss = 27052.611328125
2022-10-04 01:09:00,913 INFO Epoch = 760 Total Loss = 281.6708679199219 content Loss = 13.431930541992188 style Loss = 26823.892578125
2022-10-04 01:09:09,405 INFO Epoch = 770 Total Loss = 279.4374694824219 content Loss = 13.441920280456543 style Loss = 26599.552734375
2022-10-04 01:09:17,893 INFO Epoch = 780 Total Loss = 277.24566650390625 content Loss = 13.451927185058594 style Loss = 26379.373046875
2022-10-04 01:09:26,376 INFO Epoch = 790 Total Loss = 275.1044006347656 content Loss = 13.462079048156738 style Loss = 26164.234375
2022-10-04 01:09:34,851 INFO Epoch = 800 Total Loss = 273.0131530761719 content Loss = 13.47160530090332 style Loss = 25954.154296875
2022-10-04 01:09:43,344 INFO Epoch = 810 Total Loss = 270.9673156738281 content Loss = 13.480637550354004 style Loss = 25748.669921875
2022-10-04 01:09:51,799 INFO Epoch = 820 Total Loss = 268.9657897949219 content Loss = 13.489787101745605 style Loss = 25547.6015625
2022-10-04 01:10:00,273 INFO Epoch = 830 Total Loss = 267.0140380859375 content Loss = 13.498807907104492 style Loss = 25351.5234375
2022-10-04 01:10:08,704 INFO Epoch = 840 Total Loss = 265.09613037109375 content Loss = 13.507080078125 style Loss = 25158.90625
2022-10-04 01:10:17,238 INFO Epoch = 850 Total Loss = 263.2208557128906 content Loss = 13.515578269958496 style Loss = 24970.529296875
2022-10-04 01:10:25,753 INFO Epoch = 860 Total Loss = 261.38739013671875 content Loss = 13.524173736572266 style Loss = 24786.32421875
2022-10-04 01:10:34,301 INFO Epoch = 870 Total Loss = 259.59381103515625 content Loss = 13.532782554626465 style Loss = 24606.10546875
2022-10-04 01:10:42,783 INFO Epoch = 880 Total Loss = 257.840087890625 content Loss = 13.541803359985352 style Loss = 24429.830078125
2022-10-04 01:10:51,248 INFO Epoch = 890 Total Loss = 256.1158142089844 content Loss = 13.550373077392578 style Loss = 24256.546875
2022-10-04 01:10:59,733 INFO Epoch = 900 Total Loss = 254.42385864257812 content Loss = 13.558671951293945 style Loss = 24086.521484375
2022-10-04 01:11:08,215 INFO Epoch = 910 Total Loss = 252.77883911132812 content Loss = 13.566659927368164 style Loss = 23921.216796875
2022-10-04 01:11:16,696 INFO Epoch = 920 Total Loss = 251.17144775390625 content Loss = 13.57442569732666 style Loss = 23759.703125
2022-10-04 01:11:25,316 INFO Epoch = 930 Total Loss = 249.5976104736328 content Loss = 13.582340240478516 style Loss = 23601.52734375
2022-10-04 01:11:34,008 INFO Epoch = 940 Total Loss = 248.05369567871094 content Loss = 13.589677810668945 style Loss = 23446.40234375
2022-10-04 01:11:42,606 INFO Epoch = 950 Total Loss = 246.53643798828125 content Loss = 13.5964937210083 style Loss = 23293.99609375
2022-10-04 01:11:51,271 INFO Epoch = 960 Total Loss = 245.05148315429688 content Loss = 13.60432243347168 style Loss = 23144.71484375
2022-10-04 01:11:59,795 INFO Epoch = 970 Total Loss = 243.58993530273438 content Loss = 13.611795425415039 style Loss = 22997.8125
2022-10-04 01:12:08,318 INFO Epoch = 980 Total Loss = 242.15371704101562 content Loss = 13.61968994140625 style Loss = 22853.40234375
2022-10-04 01:12:16,830 INFO Epoch = 990 Total Loss = 240.74017333984375 content Loss = 13.6275053024292 style Loss = 22711.267578125
2022-10-04 01:12:25,324 INFO Epoch = 1000 Total Loss = 239.35362243652344 content Loss = 13.634270668029785 style Loss = 22571.935546875
2022-10-04 01:12:33,951 INFO Epoch = 1010 Total Loss = 237.98802185058594 content Loss = 13.640804290771484 style Loss = 22434.724609375
2022-10-04 01:12:42,642 INFO Epoch = 1020 Total Loss = 236.65042114257812 content Loss = 13.647942543029785 style Loss = 22300.248046875
2022-10-04 01:12:51,576 INFO Epoch = 1030 Total Loss = 235.33755493164062 content Loss = 13.655529022216797 style Loss = 22168.205078125
2022-10-04 01:13:00,174 INFO Epoch = 1040 Total Loss = 234.044921875 content Loss = 13.662823677062988 style Loss = 22038.2109375
2022-10-04 01:13:08,990 INFO Epoch = 1050 Total Loss = 232.76654052734375 content Loss = 13.6697998046875 style Loss = 21909.67578125
2022-10-04 01:13:17,861 INFO Epoch = 1060 Total Loss = 231.4991912841797 content Loss = 13.676559448242188 style Loss = 21782.263671875
2022-10-04 01:13:26,642 INFO Epoch = 1070 Total Loss = 230.25637817382812 content Loss = 13.683370590209961 style Loss = 21657.30078125
2022-10-04 01:13:35,515 INFO Epoch = 1080 Total Loss = 229.03700256347656 content Loss = 13.690727233886719 style Loss = 21534.626953125
2022-10-04 01:13:44,069 INFO Epoch = 1090 Total Loss = 227.83847045898438 content Loss = 13.69784164428711 style Loss = 21414.064453125
2022-10-04 01:13:52,644 INFO Epoch = 1100 Total Loss = 226.65882873535156 content Loss = 13.704916000366211 style Loss = 21295.390625
2022-10-04 01:14:01,412 INFO Epoch = 1110 Total Loss = 225.4905548095703 content Loss = 13.712178230285645 style Loss = 21177.837890625
2022-10-04 01:14:10,006 INFO Epoch = 1120 Total Loss = 224.34368896484375 content Loss = 13.719354629516602 style Loss = 21062.43359375
2022-10-04 01:14:18,690 INFO Epoch = 1130 Total Loss = 223.22061157226562 content Loss = 13.726749420166016 style Loss = 20949.38671875
2022-10-04 01:14:27,237 INFO Epoch = 1140 Total Loss = 222.1175994873047 content Loss = 13.73379135131836 style Loss = 20838.380859375
2022-10-04 01:14:36,053 INFO Epoch = 1150 Total Loss = 221.03614807128906 content Loss = 13.740388870239258 style Loss = 20729.57421875
2022-10-04 01:14:45,021 INFO Epoch = 1160 Total Loss = 219.97491455078125 content Loss = 13.746526718139648 style Loss = 20622.83984375
2022-10-04 01:14:53,637 INFO Epoch = 1170 Total Loss = 218.92715454101562 content Loss = 13.753145217895508 style Loss = 20517.400390625
2022-10-04 01:15:02,214 INFO Epoch = 1180 Total Loss = 217.89529418945312 content Loss = 13.759641647338867 style Loss = 20413.564453125
2022-10-04 01:15:11,028 INFO Epoch = 1190 Total Loss = 216.87649536132812 content Loss = 13.76579475402832 style Loss = 20311.072265625
2022-10-04 01:15:19,702 INFO Epoch = 1200 Total Loss = 215.87294006347656 content Loss = 13.771727561950684 style Loss = 20210.12109375
2022-10-04 01:15:28,377 INFO Epoch = 1210 Total Loss = 214.88197326660156 content Loss = 13.777446746826172 style Loss = 20110.451171875
2022-10-04 01:15:36,973 INFO Epoch = 1220 Total Loss = 213.90390014648438 content Loss = 13.782920837402344 style Loss = 20012.099609375
2022-10-04 01:15:46,002 INFO Epoch = 1230 Total Loss = 212.93838500976562 content Loss = 13.788370132446289 style Loss = 19915.00390625
2022-10-04 01:15:54,662 INFO Epoch = 1240 Total Loss = 211.98416137695312 content Loss = 13.794151306152344 style Loss = 19819.001953125
2022-10-04 01:16:03,258 INFO Epoch = 1250 Total Loss = 211.04458618164062 content Loss = 13.800043106079102 style Loss = 19724.45703125
2022-10-04 01:16:12,223 INFO Epoch = 1260 Total Loss = 210.1155242919922 content Loss = 13.805824279785156 style Loss = 19630.96875
2022-10-04 01:16:21,001 INFO Epoch = 1270 Total Loss = 209.19668579101562 content Loss = 13.81079387664795 style Loss = 19538.58984375
2022-10-04 01:16:29,755 INFO Epoch = 1280 Total Loss = 208.28953552246094 content Loss = 13.815195083618164 style Loss = 19447.435546875
2022-10-04 01:16:38,422 INFO Epoch = 1290 Total Loss = 207.39527893066406 content Loss = 13.819765090942383 style Loss = 19357.55078125
2022-10-04 01:16:46,973 INFO Epoch = 1300 Total Loss = 206.51626586914062 content Loss = 13.824544906616211 style Loss = 19269.173828125
2022-10-04 01:16:55,517 INFO Epoch = 1310 Total Loss = 205.65032958984375 content Loss = 13.82938003540039 style Loss = 19182.095703125
2022-10-04 01:17:04,068 INFO Epoch = 1320 Total Loss = 204.7971649169922 content Loss = 13.83415412902832 style Loss = 19096.30078125
2022-10-04 01:17:12,616 INFO Epoch = 1330 Total Loss = 203.9553985595703 content Loss = 13.83955192565918 style Loss = 19011.5859375
2022-10-04 01:17:21,166 INFO Epoch = 1340 Total Loss = 203.1263885498047 content Loss = 13.845307350158691 style Loss = 18928.10546875
2022-10-04 01:17:29,714 INFO Epoch = 1350 Total Loss = 202.30941772460938 content Loss = 13.850868225097656 style Loss = 18845.853515625
2022-10-04 01:17:38,266 INFO Epoch = 1360 Total Loss = 201.50840759277344 content Loss = 13.856135368347168 style Loss = 18765.228515625
2022-10-04 01:17:46,797 INFO Epoch = 1370 Total Loss = 200.71522521972656 content Loss = 13.861408233642578 style Loss = 18685.380859375
2022-10-04 01:17:55,348 INFO Epoch = 1380 Total Loss = 199.93423461914062 content Loss = 13.866347312927246 style Loss = 18606.787109375
2022-10-04 01:18:03,912 INFO Epoch = 1390 Total Loss = 199.16160583496094 content Loss = 13.871301651000977 style Loss = 18529.03125
2022-10-04 01:18:12,500 INFO Epoch = 1400 Total Loss = 198.39959716796875 content Loss = 13.876117706298828 style Loss = 18452.349609375
2022-10-04 01:18:21,063 INFO Epoch = 1410 Total Loss = 197.64517211914062 content Loss = 13.880973815917969 style Loss = 18376.419921875
2022-10-04 01:18:29,716 INFO Epoch = 1420 Total Loss = 196.90260314941406 content Loss = 13.885868072509766 style Loss = 18301.673828125
2022-10-04 01:18:38,305 INFO Epoch = 1430 Total Loss = 196.1732177734375 content Loss = 13.89122486114502 style Loss = 18228.19921875
2022-10-04 01:18:47,154 INFO Epoch = 1440 Total Loss = 195.45855712890625 content Loss = 13.896126747131348 style Loss = 18156.244140625
2022-10-04 01:19:13,202 INFO Epoch = 1450 Total Loss = 194.75494384765625 content Loss = 13.900690078735352 style Loss = 18085.42578125
2022-10-04 01:19:21,805 INFO Epoch = 1460 Total Loss = 194.06008911132812 content Loss = 13.904851913452148 style Loss = 18015.525390625
2022-10-04 01:19:30,371 INFO Epoch = 1470 Total Loss = 193.37307739257812 content Loss = 13.909048080444336 style Loss = 17946.404296875
2022-10-04 01:19:38,964 INFO Epoch = 1480 Total Loss = 192.69772338867188 content Loss = 13.913125038146973 style Loss = 17878.458984375
2022-10-04 01:19:47,516 INFO Epoch = 1490 Total Loss = 192.0325927734375 content Loss = 13.917144775390625 style Loss = 17811.544921875
2022-10-04 01:19:56,060 INFO Epoch = 1500 Total Loss = 191.3739776611328 content Loss = 13.921102523803711 style Loss = 17745.287109375
2022-10-04 01:20:04,693 INFO Epoch = 1510 Total Loss = 190.7206573486328 content Loss = 13.925324440002441 style Loss = 17679.533203125
2022-10-04 01:20:13,359 INFO Epoch = 1520 Total Loss = 190.07675170898438 content Loss = 13.929585456848145 style Loss = 17614.716796875
2022-10-04 01:20:22,034 INFO Epoch = 1530 Total Loss = 189.4416961669922 content Loss = 13.9339599609375 style Loss = 17550.7734375
2022-10-04 01:20:30,729 INFO Epoch = 1540 Total Loss = 188.81668090820312 content Loss = 13.93832015991211 style Loss = 17487.8359375
2022-10-04 01:20:39,375 INFO Epoch = 1550 Total Loss = 188.20248413085938 content Loss = 13.94186782836914 style Loss = 17426.0625
2022-10-04 01:20:47,980 INFO Epoch = 1560 Total Loss = 187.59649658203125 content Loss = 13.945804595947266 style Loss = 17365.0703125
2022-10-04 01:20:56,570 INFO Epoch = 1570 Total Loss = 186.9988555908203 content Loss = 13.949748992919922 style Loss = 17304.91015625
2022-10-04 01:21:05,194 INFO Epoch = 1580 Total Loss = 186.4098663330078 content Loss = 13.95374870300293 style Loss = 17245.611328125
2022-10-04 01:21:13,755 INFO Epoch = 1590 Total Loss = 185.8284912109375 content Loss = 13.957193374633789 style Loss = 17187.130859375
2022-10-04 01:21:22,366 INFO Epoch = 1600 Total Loss = 185.2548370361328 content Loss = 13.96125602722168 style Loss = 17129.359375
2022-10-04 01:21:30,977 INFO Epoch = 1610 Total Loss = 184.69265747070312 content Loss = 13.965795516967773 style Loss = 17072.6875
2022-10-04 01:21:39,587 INFO Epoch = 1620 Total Loss = 184.14205932617188 content Loss = 13.96995735168457 style Loss = 17017.2109375
2022-10-04 01:21:48,261 INFO Epoch = 1630 Total Loss = 183.58648681640625 content Loss = 13.974283218383789 style Loss = 16961.220703125
2022-10-04 01:21:56,860 INFO Epoch = 1640 Total Loss = 183.0550537109375 content Loss = 13.978854179382324 style Loss = 16907.62109375
2022-10-04 01:22:05,552 INFO Epoch = 1650 Total Loss = 182.52532958984375 content Loss = 13.982721328735352 style Loss = 16854.259765625
2022-10-04 01:22:14,128 INFO Epoch = 1660 Total Loss = 181.98892211914062 content Loss = 13.98670768737793 style Loss = 16800.22265625
2022-10-04 01:22:22,881 INFO Epoch = 1670 Total Loss = 181.54006958007812 content Loss = 13.991753578186035 style Loss = 16754.83203125
2022-10-04 01:22:31,840 INFO Epoch = 1680 Total Loss = 180.909423828125 content Loss = 13.993974685668945 style Loss = 16691.544921875
2022-10-04 01:22:40,586 INFO Epoch = 1690 Total Loss = 181.00662231445312 content Loss = 14.002899169921875 style Loss = 16700.373046875
2022-10-04 01:22:49,307 INFO Epoch = 1700 Total Loss = 179.8927001953125 content Loss = 14.000743865966797 style Loss = 16589.1953125
2022-10-04 01:22:58,095 INFO Epoch = 1710 Total Loss = 180.42236328125 content Loss = 13.997247695922852 style Loss = 16642.513671875
2022-10-04 01:23:06,858 INFO Epoch = 1720 Total Loss = 179.24951171875 content Loss = 14.013468742370605 style Loss = 16523.603515625
2022-10-04 01:23:15,631 INFO Epoch = 1730 Total Loss = 178.8757781982422 content Loss = 14.017779350280762 style Loss = 16485.80078125
2022-10-04 01:23:24,416 INFO Epoch = 1740 Total Loss = 179.00042724609375 content Loss = 14.00976276397705 style Loss = 16499.06640625
2022-10-04 01:23:33,184 INFO Epoch = 1750 Total Loss = 177.56260681152344 content Loss = 14.018807411193848 style Loss = 16354.37890625
2022-10-04 01:23:41,989 INFO Epoch = 1760 Total Loss = 178.65049743652344 content Loss = 14.034464836120605 style Loss = 16461.603515625
2022-10-04 01:23:50,972 INFO Epoch = 1770 Total Loss = 176.80511474609375 content Loss = 14.024847030639648 style Loss = 16278.0263671875
2022-10-04 01:23:59,716 INFO Epoch = 1780 Total Loss = 180.07833862304688 content Loss = 14.01858901977539 style Loss = 16605.974609375
2022-10-04 01:24:08,509 INFO Epoch = 1790 Total Loss = 177.45468139648438 content Loss = 14.044585227966309 style Loss = 16341.0107421875
2022-10-04 01:24:17,225 INFO Epoch = 1800 Total Loss = 175.27626037597656 content Loss = 14.037297248840332 style Loss = 16123.8974609375
2022-10-04 01:24:25,963 INFO Epoch = 1810 Total Loss = 179.95411682128906 content Loss = 14.026268005371094 style Loss = 16592.78515625
2022-10-04 01:24:34,734 INFO Epoch = 1820 Total Loss = 175.83627319335938 content Loss = 14.054344177246094 style Loss = 16178.193359375
2022-10-04 01:24:43,461 INFO Epoch = 1830 Total Loss = 173.97415161132812 content Loss = 14.04773998260498 style Loss = 15992.640625
2022-10-04 01:24:52,175 INFO Epoch = 1840 Total Loss = 177.4563446044922 content Loss = 14.039932250976562 style Loss = 16341.642578125
2022-10-04 01:25:00,871 INFO Epoch = 1850 Total Loss = 174.22128295898438 content Loss = 14.064996719360352 style Loss = 16015.6298828125
2022-10-04 01:25:09,595 INFO Epoch = 1860 Total Loss = 173.1801300048828 content Loss = 14.065896034240723 style Loss = 15911.4248046875
2022-10-04 01:25:18,312 INFO Epoch = 1870 Total Loss = 175.86367797851562 content Loss = 14.051822662353516 style Loss = 16181.185546875
2022-10-04 01:25:26,995 INFO Epoch = 1880 Total Loss = 171.89599609375 content Loss = 14.06829833984375 style Loss = 15782.76953125
2022-10-04 01:25:35,687 INFO Epoch = 1890 Total Loss = 173.18655395507812 content Loss = 14.080521583557129 style Loss = 15910.603515625
2022-10-04 01:25:44,399 INFO Epoch = 1900 Total Loss = 174.05738830566406 content Loss = 14.063413619995117 style Loss = 15999.3984375
2022-10-04 01:25:53,083 INFO Epoch = 1910 Total Loss = 170.88186645507812 content Loss = 14.076220512390137 style Loss = 15680.564453125
2022-10-04 01:26:02,047 INFO Epoch = 1920 Total Loss = 171.63821411132812 content Loss = 14.090034484863281 style Loss = 15754.81640625
2022-10-04 01:30:46,087 INFO Epoch = 1930 Total Loss = 173.3831329345703 content Loss = 14.072784423828125 style Loss = 15931.03515625
2022-10-04 01:30:54,618 INFO Epoch = 1940 Total Loss = 170.0040740966797 content Loss = 14.084598541259766 style Loss = 15591.947265625
2022-10-04 01:31:03,179 INFO Epoch = 1950 Total Loss = 171.4821319580078 content Loss = 14.10318374633789 style Loss = 15737.89453125
2022-10-04 01:31:12,022 INFO Epoch = 1960 Total Loss = 171.88250732421875 content Loss = 14.084089279174805 style Loss = 15779.841796875
2022-10-04 01:31:20,832 INFO Epoch = 1970 Total Loss = 168.55645751953125 content Loss = 14.096942901611328 style Loss = 15445.951171875
2022-10-04 01:31:29,496 INFO Epoch = 1980 Total Loss = 171.37350463867188 content Loss = 14.115108489990234 style Loss = 15725.83984375
2022-10-04 01:31:38,104 INFO Epoch = 1990 Total Loss = 169.3415069580078 content Loss = 14.096443176269531 style Loss = 15524.505859375
2022-10-04 01:31:46,686 INFO Epoch = 2000 Total Loss = 179.83584594726562 content Loss = 14.083770751953125 style Loss = 16575.208984375
2022-10-04 01:31:55,294 INFO Epoch = 2010 Total Loss = 170.83290100097656 content Loss = 14.12228012084961 style Loss = 15671.0625
2022-10-04 01:32:03,894 INFO Epoch = 2020 Total Loss = 168.26666259765625 content Loss = 14.10463809967041 style Loss = 15416.203125
2022-10-04 01:32:12,510 INFO Epoch = 2030 Total Loss = 169.57797241210938 content Loss = 14.128936767578125 style Loss = 15544.904296875
2022-10-04 01:32:21,100 INFO Epoch = 2040 Total Loss = 166.2328338623047 content Loss = 14.116722106933594 style Loss = 15211.611328125
2022-10-04 01:32:29,720 INFO Epoch = 2050 Total Loss = 184.21585083007812 content Loss = 14.095752716064453 style Loss = 17012.009765625
2022-10-04 01:32:38,307 INFO Epoch = 2060 Total Loss = 173.97653198242188 content Loss = 14.145801544189453 style Loss = 15983.0732421875
2022-10-04 01:32:46,913 INFO Epoch = 2070 Total Loss = 169.11959838867188 content Loss = 14.11721420288086 style Loss = 15500.2392578125
2022-10-04 01:32:55,517 INFO Epoch = 2080 Total Loss = 167.0885772705078 content Loss = 14.143787384033203 style Loss = 15294.48046875
2022-10-04 01:33:04,138 INFO Epoch = 2090 Total Loss = 165.88291931152344 content Loss = 14.129678726196289 style Loss = 15175.3232421875
2022-10-04 01:33:12,761 INFO Epoch = 2100 Total Loss = 167.91062927246094 content Loss = 14.129484176635742 style Loss = 15378.115234375
2022-10-04 01:33:21,362 INFO Epoch = 2110 Total Loss = 167.53933715820312 content Loss = 14.157903671264648 style Loss = 15338.14453125
2022-10-04 01:33:29,927 INFO Epoch = 2120 Total Loss = 163.3163604736328 content Loss = 14.146942138671875 style Loss = 14916.9423828125
2022-10-04 01:33:38,550 INFO Epoch = 2130 Total Loss = 173.42202758789062 content Loss = 14.13032341003418 style Loss = 15929.171875
2022-10-04 01:40:09,562 INFO Epoch = 2140 Total Loss = 165.30963134765625 content Loss = 14.163477897644043 style Loss = 15114.615234375
2022-10-04 01:40:18,198 INFO Epoch = 2150 Total Loss = 162.73471069335938 content Loss = 14.151519775390625 style Loss = 14858.3193359375
2022-10-04 01:40:26,991 INFO Epoch = 2160 Total Loss = 164.93775939941406 content Loss = 14.148503303527832 style Loss = 15078.92578125
2022-10-04 01:40:35,712 INFO Epoch = 2170 Total Loss = 165.46124267578125 content Loss = 14.174531936645508 style Loss = 15128.669921875
2022-10-04 01:40:44,189 INFO Epoch = 2180 Total Loss = 164.63291931152344 content Loss = 14.174933433532715 style Loss = 15045.7978515625
2022-10-04 01:40:52,878 INFO Epoch = 2190 Total Loss = 165.64186096191406 content Loss = 14.152153015136719 style Loss = 15148.970703125
2022-10-04 01:41:01,473 INFO Epoch = 2200 Total Loss = 165.41697692871094 content Loss = 14.183614730834961 style Loss = 15123.333984375
2022-10-04 01:41:10,218 INFO Epoch = 2210 Total Loss = 160.9547882080078 content Loss = 14.175897598266602 style Loss = 14677.890625
2022-10-04 01:41:18,874 INFO Epoch = 2220 Total Loss = 165.6198272705078 content Loss = 14.160983085632324 style Loss = 15145.8837890625
2022-10-04 01:41:27,414 INFO Epoch = 2230 Total Loss = 162.23873901367188 content Loss = 14.188698768615723 style Loss = 14805.00390625
2022-10-04 01:41:35,950 INFO Epoch = 2240 Total Loss = 173.46226501464844 content Loss = 14.204962730407715 style Loss = 15925.7314453125
2022-10-04 01:41:44,508 INFO Epoch = 2250 Total Loss = 166.7939453125 content Loss = 14.165938377380371 style Loss = 15262.7998046875
2022-10-04 01:41:53,021 INFO Epoch = 2260 Total Loss = 164.3386688232422 content Loss = 14.200336456298828 style Loss = 15013.8330078125
2022-10-04 01:42:01,545 INFO Epoch = 2270 Total Loss = 160.5444793701172 content Loss = 14.179861068725586 style Loss = 14636.4619140625
2022-10-04 01:42:10,066 INFO Epoch = 2280 Total Loss = 167.03546142578125 content Loss = 14.171496391296387 style Loss = 15286.3984375
2022-10-04 01:42:18,570 INFO Epoch = 2290 Total Loss = 163.477783203125 content Loss = 14.207058906555176 style Loss = 14927.072265625
2022-10-04 01:42:27,232 INFO Epoch = 2300 Total Loss = 158.3927764892578 content Loss = 14.194236755371094 style Loss = 14419.853515625
2022-10-04 01:42:35,927 INFO Epoch = 2310 Total Loss = 172.47999572753906 content Loss = 14.17495346069336 style Loss = 15830.5048828125
2022-10-04 01:42:44,543 INFO Epoch = 2320 Total Loss = 160.88450622558594 content Loss = 14.20854663848877 style Loss = 14667.595703125
2022-10-04 01:42:53,361 INFO Epoch = 2330 Total Loss = 157.6923828125 content Loss = 14.201682090759277 style Loss = 14349.0703125
2022-10-04 01:43:02,189 INFO Epoch = 2340 Total Loss = 162.8966064453125 content Loss = 14.192455291748047 style Loss = 14870.4140625
2022-10-04 01:43:10,961 INFO Epoch = 2350 Total Loss = 157.70407104492188 content Loss = 14.208889961242676 style Loss = 14349.517578125
2022-10-04 01:43:19,590 INFO Epoch = 2360 Total Loss = 191.55752563476562 content Loss = 14.249692916870117 style Loss = 17730.78515625
2022-10-04 01:43:28,092 INFO Epoch = 2370 Total Loss = 283.1028137207031 content Loss = 14.128166198730469 style Loss = 26897.462890625
2022-10-04 01:43:36,651 INFO Epoch = 2380 Total Loss = 170.77015686035156 content Loss = 14.212919235229492 style Loss = 15655.72265625
2022-10-04 01:43:45,220 INFO Epoch = 2390 Total Loss = 169.47625732421875 content Loss = 14.224404335021973 style Loss = 15525.1865234375
2022-10-04 01:43:53,721 INFO Epoch = 2400 Total Loss = 164.15380859375 content Loss = 14.202275276184082 style Loss = 14995.154296875
2022-10-04 01:44:02,384 INFO Epoch = 2410 Total Loss = 159.2873992919922 content Loss = 14.21583366394043 style Loss = 14507.15625
2022-10-04 01:44:11,069 INFO Epoch = 2420 Total Loss = 157.72311401367188 content Loss = 14.228548049926758 style Loss = 14349.45703125
2022-10-04 01:44:19,751 INFO Epoch = 2430 Total Loss = 156.78131103515625 content Loss = 14.233963012695312 style Loss = 14254.734375
2022-10-04 01:44:28,447 INFO Epoch = 2440 Total Loss = 155.98519897460938 content Loss = 14.236352920532227 style Loss = 14174.884765625
2022-10-04 01:44:37,146 INFO Epoch = 2450 Total Loss = 155.3619384765625 content Loss = 14.238568305969238 style Loss = 14112.3369140625
2022-10-04 01:44:45,812 INFO Epoch = 2460 Total Loss = 154.8373565673828 content Loss = 14.242395401000977 style Loss = 14059.49609375
2022-10-04 01:44:54,471 INFO Epoch = 2470 Total Loss = 154.8682403564453 content Loss = 14.243951797485352 style Loss = 14062.4287109375
2022-10-04 01:45:03,086 INFO Epoch = 2480 Total Loss = 155.91531372070312 content Loss = 14.243635177612305 style Loss = 14167.16796875
2022-10-04 01:45:11,714 INFO Epoch = 2490 Total Loss = 154.9051971435547 content Loss = 14.259973526000977 style Loss = 14064.5234375
2022-10-04 01:45:20,338 INFO Epoch = 2500 Total Loss = 153.22329711914062 content Loss = 14.256535530090332 style Loss = 13896.6767578125
2022-10-04 01:45:28,999 INFO Epoch = 2510 Total Loss = 156.3265838623047 content Loss = 14.248815536499023 style Loss = 14207.775390625
2022-10-04 01:45:37,712 INFO Epoch = 2520 Total Loss = 152.8740997314453 content Loss = 14.262553215026855 style Loss = 13861.1533203125
2022-10-04 01:45:46,421 INFO Epoch = 2530 Total Loss = 153.7849884033203 content Loss = 14.2725191116333 style Loss = 13951.248046875
2022-10-04 01:45:55,108 INFO Epoch = 2540 Total Loss = 153.73130798339844 content Loss = 14.266744613647461 style Loss = 13946.45703125
2022-10-04 01:46:03,872 INFO Epoch = 2550 Total Loss = 180.74703979492188 content Loss = 14.23524284362793 style Loss = 16651.1796875
2022-10-04 01:46:12,576 INFO Epoch = 2560 Total Loss = 179.36219787597656 content Loss = 14.299047470092773 style Loss = 16506.31640625
2022-10-04 01:46:21,307 INFO Epoch = 2570 Total Loss = 152.4728546142578 content Loss = 14.275314331054688 style Loss = 13819.7548828125
2022-10-04 01:46:30,058 INFO Epoch = 2580 Total Loss = 154.27955627441406 content Loss = 14.265633583068848 style Loss = 14001.392578125
2022-10-04 01:46:38,841 INFO Epoch = 2590 Total Loss = 151.45530700683594 content Loss = 14.27530288696289 style Loss = 13718.0009765625
2022-10-04 01:46:47,663 INFO Epoch = 2600 Total Loss = 152.79638671875 content Loss = 14.283540725708008 style Loss = 13851.283203125
2022-10-04 01:46:56,386 INFO Epoch = 2610 Total Loss = 169.6617889404297 content Loss = 14.261886596679688 style Loss = 15539.9912109375
2022-10-04 01:47:05,281 INFO Epoch = 2620 Total Loss = 155.23074340820312 content Loss = 14.300512313842773 style Loss = 14093.0224609375
2022-10-04 01:47:13,997 INFO Epoch = 2630 Total Loss = 149.9564971923828 content Loss = 14.290045738220215 style Loss = 13566.64453125
2022-10-04 01:47:22,850 INFO Epoch = 2640 Total Loss = 149.6837158203125 content Loss = 14.294136047363281 style Loss = 13538.958984375
2022-10-04 01:47:31,694 INFO Epoch = 2650 Total Loss = 149.6755828857422 content Loss = 14.293306350708008 style Loss = 13538.2275390625
2022-10-04 01:47:40,404 INFO Epoch = 2660 Total Loss = 240.16429138183594 content Loss = 14.240296363830566 style Loss = 22592.3984375
2022-10-04 01:47:49,186 INFO Epoch = 2670 Total Loss = 163.6629638671875 content Loss = 14.317975997924805 style Loss = 14934.4990234375
2022-10-04 01:47:57,944 INFO Epoch = 2680 Total Loss = 152.25352478027344 content Loss = 14.299556732177734 style Loss = 13795.396484375
2022-10-04 01:48:06,727 INFO Epoch = 2690 Total Loss = 151.25274658203125 content Loss = 14.300220489501953 style Loss = 13695.251953125
2022-10-04 01:48:15,476 INFO Epoch = 2700 Total Loss = 151.03726196289062 content Loss = 14.303044319152832 style Loss = 13673.421875
2022-10-04 01:48:24,296 INFO Epoch = 2710 Total Loss = 149.50726318359375 content Loss = 14.310322761535645 style Loss = 13519.6943359375
2022-10-04 01:48:33,066 INFO Epoch = 2720 Total Loss = 149.67495727539062 content Loss = 14.321751594543457 style Loss = 13535.3203125
2022-10-04 01:48:41,655 INFO Epoch = 2730 Total Loss = 161.16969299316406 content Loss = 14.339308738708496 style Loss = 14683.0390625
2022-10-04 01:48:50,237 INFO Epoch = 2740 Total Loss = 151.99203491210938 content Loss = 14.30809211730957 style Loss = 13768.39453125
2022-10-04 01:48:58,831 INFO Epoch = 2750 Total Loss = 149.4401397705078 content Loss = 14.332846641540527 style Loss = 13510.728515625
2022-10-04 01:49:07,379 INFO Epoch = 2760 Total Loss = 148.57138061523438 content Loss = 14.3179349899292 style Loss = 13425.3447265625
2022-10-04 01:49:15,900 INFO Epoch = 2770 Total Loss = 147.27386474609375 content Loss = 14.324329376220703 style Loss = 13294.953125
2022-10-04 01:49:24,441 INFO Epoch = 2780 Total Loss = 148.15975952148438 content Loss = 14.340814590454102 style Loss = 13381.89453125
2022-10-04 01:49:32,986 INFO Epoch = 2790 Total Loss = 182.67445373535156 content Loss = 14.365782737731934 style Loss = 16830.8671875
2022-10-04 01:49:41,527 INFO Epoch = 2800 Total Loss = 147.6805419921875 content Loss = 14.328533172607422 style Loss = 13335.2021484375
2022-10-04 01:49:50,050 INFO Epoch = 2810 Total Loss = 151.45413208007812 content Loss = 14.324423789978027 style Loss = 13712.970703125
2022-10-04 01:49:58,555 INFO Epoch = 2820 Total Loss = 146.1310577392578 content Loss = 14.336322784423828 style Loss = 13179.474609375
2022-10-04 01:50:07,175 INFO Epoch = 2830 Total Loss = 146.6160125732422 content Loss = 14.34162712097168 style Loss = 13227.4375
2022-10-04 01:50:15,791 INFO Epoch = 2840 Total Loss = 158.758056640625 content Loss = 14.322057723999023 style Loss = 14443.599609375
2022-10-04 01:50:24,290 INFO Epoch = 2850 Total Loss = 153.70143127441406 content Loss = 14.357698440551758 style Loss = 13934.373046875
2022-10-04 01:50:33,014 INFO Epoch = 2860 Total Loss = 159.57546997070312 content Loss = 14.323969841003418 style Loss = 14525.150390625
2022-10-04 01:50:41,748 INFO Epoch = 2870 Total Loss = 146.61563110351562 content Loss = 14.353622436523438 style Loss = 13226.201171875
2022-10-04 01:50:50,455 INFO Epoch = 2880 Total Loss = 145.71347045898438 content Loss = 14.357748031616211 style Loss = 13135.572265625
2022-10-04 01:50:59,179 INFO Epoch = 2890 Total Loss = 144.79864501953125 content Loss = 14.35335922241211 style Loss = 13044.529296875
2022-10-04 01:51:07,882 INFO Epoch = 2900 Total Loss = 144.67880249023438 content Loss = 14.358797073364258 style Loss = 13032.0009765625
2022-10-04 01:51:16,596 INFO Epoch = 2910 Total Loss = 224.036376953125 content Loss = 14.409017562866211 style Loss = 20962.736328125
2022-10-04 01:51:25,312 INFO Epoch = 2920 Total Loss = 178.2196807861328 content Loss = 14.346973419189453 style Loss = 16387.2734375
2022-10-04 01:51:34,025 INFO Epoch = 2930 Total Loss = 168.33152770996094 content Loss = 14.351585388183594 style Loss = 15397.994140625
2022-10-04 01:51:42,654 INFO Epoch = 2940 Total Loss = 146.73175048828125 content Loss = 14.354741096496582 style Loss = 13237.701171875
2022-10-04 01:51:51,306 INFO Epoch = 2950 Total Loss = 148.0899658203125 content Loss = 14.359848976135254 style Loss = 13373.01171875
2022-10-04 01:51:59,955 INFO Epoch = 2960 Total Loss = 144.7750244140625 content Loss = 14.370144844055176 style Loss = 13040.4873046875
2022-10-04 01:52:08,599 INFO Epoch = 2970 Total Loss = 154.06829833984375 content Loss = 14.388012886047363 style Loss = 13968.0283203125
2022-10-04 01:52:17,241 INFO Epoch = 2980 Total Loss = 143.7312469482422 content Loss = 14.374191284179688 style Loss = 12935.7041015625
2022-10-04 01:52:25,896 INFO Epoch = 2990 Total Loss = 143.11514282226562 content Loss = 14.377126693725586 style Loss = 12873.802734375
2022-10-04 01:52:34,520 INFO Epoch = 3000 Total Loss = 142.80825805664062 content Loss = 14.382651329040527 style Loss = 12842.560546875
2022-10-04 01:52:43,317 INFO Epoch = 3010 Total Loss = 144.86572265625 content Loss = 14.373167991638184 style Loss = 13049.2548828125
2022-10-04 01:52:51,975 INFO Epoch = 3020 Total Loss = 142.11146545410156 content Loss = 14.3846435546875 style Loss = 12772.6826171875
2022-10-04 01:53:00,636 INFO Epoch = 3030 Total Loss = 148.7610321044922 content Loss = 14.404786109924316 style Loss = 13435.625
2022-10-04 01:53:09,357 INFO Epoch = 3040 Total Loss = 147.22506713867188 content Loss = 14.397128105163574 style Loss = 13282.7939453125
2022-10-04 01:53:18,075 INFO Epoch = 3050 Total Loss = 144.0625762939453 content Loss = 14.398876190185547 style Loss = 12966.369140625
2022-10-04 01:53:26,816 INFO Epoch = 3060 Total Loss = 145.5370635986328 content Loss = 14.381662368774414 style Loss = 13115.5400390625
2022-10-04 01:53:35,560 INFO Epoch = 3070 Total Loss = 143.19662475585938 content Loss = 14.405585289001465 style Loss = 12879.1044921875
2022-10-04 01:53:44,400 INFO Epoch = 3080 Total Loss = 142.34381103515625 content Loss = 14.392572402954102 style Loss = 12795.125
2022-10-04 01:53:53,265 INFO Epoch = 3090 Total Loss = 145.6351318359375 content Loss = 14.395779609680176 style Loss = 13123.935546875
2022-10-04 01:54:02,135 INFO Epoch = 3100 Total Loss = 160.29200744628906 content Loss = 14.381855964660645 style Loss = 14591.015625
2022-10-04 01:54:10,946 INFO Epoch = 3110 Total Loss = 244.08070373535156 content Loss = 14.363764762878418 style Loss = 22971.697265625
2022-10-04 01:54:19,732 INFO Epoch = 3120 Total Loss = 175.89163208007812 content Loss = 14.375950813293457 style Loss = 16151.56640625
2022-10-04 01:54:28,452 INFO Epoch = 3130 Total Loss = 148.08200073242188 content Loss = 14.407018661499023 style Loss = 13367.4990234375
2022-10-04 01:54:37,156 INFO Epoch = 3140 Total Loss = 142.01010131835938 content Loss = 14.405734062194824 style Loss = 12760.4365234375
2022-10-04 01:54:45,853 INFO Epoch = 3150 Total Loss = 142.2878875732422 content Loss = 14.41677474975586 style Loss = 12787.1103515625
2022-10-04 01:54:54,659 INFO Epoch = 3160 Total Loss = 140.83497619628906 content Loss = 14.417746543884277 style Loss = 12641.7236328125
2022-10-04 01:55:03,326 INFO Epoch = 3170 Total Loss = 143.8946533203125 content Loss = 14.432413101196289 style Loss = 12946.2255859375
2022-10-04 01:55:12,187 INFO Epoch = 3180 Total Loss = 153.71649169921875 content Loss = 14.444843292236328 style Loss = 13927.1630859375
2022-10-04 01:55:20,957 INFO Epoch = 3190 Total Loss = 141.52793884277344 content Loss = 14.431058883666992 style Loss = 12709.6884765625
2022-10-04 01:55:29,804 INFO Epoch = 3200 Total Loss = 143.50946044921875 content Loss = 14.413087844848633 style Loss = 12909.63671875
2022-10-04 01:55:38,499 INFO Epoch = 3210 Total Loss = 140.3949737548828 content Loss = 14.435062408447266 style Loss = 12595.990234375
2022-10-04 01:55:47,412 INFO Epoch = 3220 Total Loss = 140.01011657714844 content Loss = 14.42550277709961 style Loss = 12558.462890625
2022-10-04 01:55:56,087 INFO Epoch = 3230 Total Loss = 138.67442321777344 content Loss = 14.437116622924805 style Loss = 12423.7294921875
2022-10-04 01:56:05,097 INFO Epoch = 3240 Total Loss = 158.94143676757812 content Loss = 14.464988708496094 style Loss = 14447.64453125
2022-10-04 01:56:13,917 INFO Epoch = 3250 Total Loss = 152.15115356445312 content Loss = 14.420828819274902 style Loss = 13773.033203125
2022-10-04 01:56:22,619 INFO Epoch = 3260 Total Loss = 145.69497680664062 content Loss = 14.452857971191406 style Loss = 13124.2119140625
2022-10-04 01:56:31,261 INFO Epoch = 3270 Total Loss = 142.1387939453125 content Loss = 14.437066078186035 style Loss = 12770.1728515625
2022-10-04 01:56:39,954 INFO Epoch = 3280 Total Loss = 138.46592712402344 content Loss = 14.444738388061523 style Loss = 12402.1181640625
2022-10-04 01:56:48,712 INFO Epoch = 3290 Total Loss = 138.36074829101562 content Loss = 14.449146270751953 style Loss = 12391.1591796875
2022-10-04 01:56:57,523 INFO Epoch = 3300 Total Loss = 183.78427124023438 content Loss = 14.490407943725586 style Loss = 16929.38671875
2022-10-04 01:57:06,430 INFO Epoch = 3310 Total Loss = 174.4482421875 content Loss = 14.42120361328125 style Loss = 16002.7041015625
2022-10-04 01:57:15,098 INFO Epoch = 3320 Total Loss = 154.90806579589844 content Loss = 14.45096206665039 style Loss = 14045.7109375
2022-10-04 01:57:23,735 INFO Epoch = 3330 Total Loss = 143.04249572753906 content Loss = 14.441631317138672 style Loss = 12860.0859375
2022-10-04 01:57:32,464 INFO Epoch = 3340 Total Loss = 139.0076904296875 content Loss = 14.454890251159668 style Loss = 12455.2802734375
2022-10-04 01:57:41,241 INFO Epoch = 3350 Total Loss = 138.07980346679688 content Loss = 14.45790958404541 style Loss = 12362.189453125
2022-10-04 01:57:49,869 INFO Epoch = 3360 Total Loss = 144.70315551757812 content Loss = 14.46959400177002 style Loss = 13023.35546875
2022-10-04 01:57:58,470 INFO Epoch = 3370 Total Loss = 137.4348907470703 content Loss = 14.466306686401367 style Loss = 12296.859375
2022-10-04 01:58:07,048 INFO Epoch = 3380 Total Loss = 174.07672119140625 content Loss = 14.49821662902832 style Loss = 15957.8505859375
2022-10-04 01:58:15,634 INFO Epoch = 3390 Total Loss = 190.1758575439453 content Loss = 14.419626235961914 style Loss = 17575.625
2022-10-04 01:58:24,215 INFO Epoch = 3400 Total Loss = 148.9606475830078 content Loss = 14.447522163391113 style Loss = 13451.3125
2022-10-04 01:58:32,871 INFO Epoch = 3410 Total Loss = 149.7437744140625 content Loss = 14.446383476257324 style Loss = 13529.7412109375
2022-10-04 01:58:41,489 INFO Epoch = 3420 Total Loss = 139.56069946289062 content Loss = 14.461520195007324 style Loss = 12509.91796875
2022-10-04 01:58:50,237 INFO Epoch = 3430 Total Loss = 138.09414672851562 content Loss = 14.471977233886719 style Loss = 12362.2177734375
2022-10-04 01:58:58,881 INFO Epoch = 3440 Total Loss = 137.57131958007812 content Loss = 14.466440200805664 style Loss = 12310.4892578125
2022-10-04 01:59:07,500 INFO Epoch = 3450 Total Loss = 140.3789520263672 content Loss = 14.467865943908691 style Loss = 12591.1083984375
2022-10-04 01:59:16,131 INFO Epoch = 3460 Total Loss = 136.72543334960938 content Loss = 14.482375144958496 style Loss = 12224.3056640625
2022-10-04 01:59:24,675 INFO Epoch = 3470 Total Loss = 145.4132537841797 content Loss = 14.499871253967285 style Loss = 13091.33984375
2022-10-04 01:59:33,380 INFO Epoch = 3480 Total Loss = 143.29002380371094 content Loss = 14.475866317749023 style Loss = 12881.4169921875
2022-10-04 01:59:42,030 INFO Epoch = 3490 Total Loss = 140.17083740234375 content Loss = 14.494285583496094 style Loss = 12567.65625
2022-10-04 01:59:50,652 INFO Epoch = 3500 Total Loss = 144.36459350585938 content Loss = 14.469294548034668 style Loss = 12989.5302734375
2022-10-04 01:59:59,275 INFO Epoch = 3510 Total Loss = 137.18142700195312 content Loss = 14.496371269226074 style Loss = 12268.505859375
2022-10-04 02:00:07,868 INFO Epoch = 3520 Total Loss = 136.4171905517578 content Loss = 14.486124038696289 style Loss = 12193.107421875
2022-10-04 02:00:16,505 INFO Epoch = 3530 Total Loss = 138.00331115722656 content Loss = 14.500696182250977 style Loss = 12350.2626953125
2022-10-04 02:00:25,193 INFO Epoch = 3540 Total Loss = 159.0968017578125 content Loss = 14.504745483398438 style Loss = 14459.2060546875
2022-10-04 02:00:33,823 INFO Epoch = 3550 Total Loss = 401.8644104003906 content Loss = 14.414982795715332 style Loss = 38744.94140625
2022-10-04 02:00:42,415 INFO Epoch = 3560 Total Loss = 240.82716369628906 content Loss = 14.444479942321777 style Loss = 22638.267578125
2022-10-04 02:00:51,038 INFO Epoch = 3570 Total Loss = 150.69219970703125 content Loss = 14.476719856262207 style Loss = 13621.5478515625
2022-10-04 02:00:59,814 INFO Epoch = 3580 Total Loss = 150.6349334716797 content Loss = 14.496719360351562 style Loss = 13613.8212890625
2022-10-04 02:01:08,585 INFO Epoch = 3590 Total Loss = 140.07498168945312 content Loss = 14.487482070922852 style Loss = 12558.7509765625
2022-10-04 02:01:17,176 INFO Epoch = 3600 Total Loss = 148.60195922851562 content Loss = 14.484516143798828 style Loss = 13411.7451171875
2022-10-04 02:01:25,813 INFO Epoch = 3610 Total Loss = 137.9881134033203 content Loss = 14.511634826660156 style Loss = 12347.6474609375
2022-10-04 02:01:34,451 INFO Epoch = 3620 Total Loss = 135.7252655029297 content Loss = 14.511144638061523 style Loss = 12121.4130859375
2022-10-04 02:01:43,095 INFO Epoch = 3630 Total Loss = 136.91796875 content Loss = 14.508275985717773 style Loss = 12240.9697265625
2022-10-04 02:01:51,659 INFO Epoch = 3640 Total Loss = 134.6762237548828 content Loss = 14.515719413757324 style Loss = 12016.05078125
2022-10-04 02:02:00,302 INFO Epoch = 3650 Total Loss = 134.7009735107422 content Loss = 14.52259349822998 style Loss = 12017.8388671875
2022-10-04 02:02:08,907 INFO Epoch = 3660 Total Loss = 188.8620147705078 content Loss = 14.558037757873535 style Loss = 17430.396484375
2022-10-04 02:02:17,723 INFO Epoch = 3670 Total Loss = 147.70608520507812 content Loss = 14.501556396484375 style Loss = 13320.453125
2022-10-04 02:02:26,306 INFO Epoch = 3680 Total Loss = 139.5780792236328 content Loss = 14.511113166809082 style Loss = 12506.697265625
2022-10-04 02:02:34,887 INFO Epoch = 3690 Total Loss = 134.08103942871094 content Loss = 14.530096054077148 style Loss = 11955.09375
2022-10-04 02:02:43,478 INFO Epoch = 3700 Total Loss = 134.05197143554688 content Loss = 14.532851219177246 style Loss = 11951.912109375
2022-10-04 02:02:52,093 INFO Epoch = 3710 Total Loss = 133.17306518554688 content Loss = 14.528182983398438 style Loss = 11864.48828125
2022-10-04 02:03:00,718 INFO Epoch = 3720 Total Loss = 133.07225036621094 content Loss = 14.532148361206055 style Loss = 11854.0107421875
2022-10-04 02:03:09,282 INFO Epoch = 3730 Total Loss = 165.8455810546875 content Loss = 14.561433792114258 style Loss = 15128.4150390625
2022-10-04 02:03:17,817 INFO Epoch = 3740 Total Loss = 167.85333251953125 content Loss = 14.52772045135498 style Loss = 15332.560546875
2022-10-04 02:03:26,317 INFO Epoch = 3750 Total Loss = 137.2747039794922 content Loss = 14.526633262634277 style Loss = 12274.8076171875
2022-10-04 02:03:35,030 INFO Epoch = 3760 Total Loss = 136.2832794189453 content Loss = 14.541471481323242 style Loss = 12174.181640625
2022-10-04 02:03:43,732 INFO Epoch = 3770 Total Loss = 135.1425018310547 content Loss = 14.541582107543945 style Loss = 12060.0927734375
2022-10-04 02:03:52,421 INFO Epoch = 3780 Total Loss = 133.81784057617188 content Loss = 14.539897918701172 style Loss = 11927.79296875
2022-10-04 02:04:01,117 INFO Epoch = 3790 Total Loss = 133.03424072265625 content Loss = 14.542078018188477 style Loss = 11849.216796875
2022-10-04 02:04:09,800 INFO Epoch = 3800 Total Loss = 132.8690185546875 content Loss = 14.545299530029297 style Loss = 11832.3720703125
2022-10-04 02:04:18,480 INFO Epoch = 3810 Total Loss = 162.3644561767578 content Loss = 14.561539649963379 style Loss = 14780.2919921875
2022-10-04 02:04:27,424 INFO Epoch = 3820 Total Loss = 146.283447265625 content Loss = 14.522436141967773 style Loss = 13176.1025390625
2022-10-04 02:04:36,213 INFO Epoch = 3830 Total Loss = 133.0662841796875 content Loss = 14.54925537109375 style Loss = 11851.703125
2022-10-04 02:04:44,935 INFO Epoch = 3840 Total Loss = 134.62643432617188 content Loss = 14.546092987060547 style Loss = 12008.033203125
2022-10-04 02:04:53,662 INFO Epoch = 3850 Total Loss = 133.82904052734375 content Loss = 14.554679870605469 style Loss = 11927.4365234375
2022-10-04 02:05:02,340 INFO Epoch = 3860 Total Loss = 165.2058868408203 content Loss = 14.58119010925293 style Loss = 15062.4697265625
2022-10-04 02:05:11,051 INFO Epoch = 3870 Total Loss = 164.3757781982422 content Loss = 14.523751258850098 style Loss = 14985.203125
2022-10-04 02:05:20,077 INFO Epoch = 3880 Total Loss = 138.0443878173828 content Loss = 14.551651000976562 style Loss = 12349.2734375
2022-10-04 02:05:28,958 INFO Epoch = 3890 Total Loss = 133.20143127441406 content Loss = 14.55062484741211 style Loss = 11865.0810546875
2022-10-04 02:05:37,683 INFO Epoch = 3900 Total Loss = 135.368408203125 content Loss = 14.561655044555664 style Loss = 12080.67578125
2022-10-04 02:05:46,376 INFO Epoch = 3910 Total Loss = 173.7377166748047 content Loss = 14.575565338134766 style Loss = 15916.2158203125
2022-10-04 02:05:55,062 INFO Epoch = 3920 Total Loss = 164.36940002441406 content Loss = 14.520055770874023 style Loss = 14984.935546875
2022-10-04 02:06:03,868 INFO Epoch = 3930 Total Loss = 132.82009887695312 content Loss = 14.559484481811523 style Loss = 11826.060546875
2022-10-04 02:06:12,585 INFO Epoch = 3940 Total Loss = 135.6519775390625 content Loss = 14.557397842407227 style Loss = 12109.45703125
2022-10-04 02:06:21,298 INFO Epoch = 3950 Total Loss = 131.36915588378906 content Loss = 14.551241874694824 style Loss = 11681.7919921875
2022-10-04 02:06:29,985 INFO Epoch = 3960 Total Loss = 157.26107788085938 content Loss = 14.526935577392578 style Loss = 14273.4140625
2022-10-04 02:06:38,744 INFO Epoch = 3970 Total Loss = 138.28025817871094 content Loss = 14.5706787109375 style Loss = 12370.9580078125
2022-10-04 02:06:47,421 INFO Epoch = 3980 Total Loss = 136.37960815429688 content Loss = 14.552507400512695 style Loss = 12182.7109375
2022-10-04 02:06:56,066 INFO Epoch = 3990 Total Loss = 133.640869140625 content Loss = 14.57124137878418 style Loss = 11906.962890625
2022-10-04 02:07:04,698 INFO Epoch = 4000 Total Loss = 146.57943725585938 content Loss = 14.576313018798828 style Loss = 13200.3115234375
2022-10-04 02:07:13,455 INFO Epoch = 4010 Total Loss = 144.6346893310547 content Loss = 14.575353622436523 style Loss = 13005.9345703125
2022-10-04 02:07:22,122 INFO Epoch = 4020 Total Loss = 146.18414306640625 content Loss = 14.579018592834473 style Loss = 13160.513671875
2022-10-04 02:07:30,791 INFO Epoch = 4030 Total Loss = 137.910888671875 content Loss = 14.579980850219727 style Loss = 12333.08984375
2022-10-04 02:07:39,577 INFO Epoch = 4040 Total Loss = 139.63125610351562 content Loss = 14.57889175415039 style Loss = 12505.236328125
2022-10-04 02:07:48,358 INFO Epoch = 4050 Total Loss = 133.10450744628906 content Loss = 14.563488960266113 style Loss = 11854.1015625
2022-10-04 02:07:57,206 INFO Epoch = 4060 Total Loss = 141.82513427734375 content Loss = 14.552413940429688 style Loss = 12727.2734375
2022-10-04 02:08:05,869 INFO Epoch = 4070 Total Loss = 158.53421020507812 content Loss = 14.547561645507812 style Loss = 14398.6650390625
2022-10-04 02:08:14,709 INFO Epoch = 4080 Total Loss = 136.14776611328125 content Loss = 14.55650520324707 style Loss = 12159.125
2022-10-04 02:08:23,550 INFO Epoch = 4090 Total Loss = 138.1966094970703 content Loss = 14.579599380493164 style Loss = 12361.7021484375
2022-10-04 02:08:32,196 INFO Epoch = 4100 Total Loss = 136.72706604003906 content Loss = 14.574390411376953 style Loss = 12215.267578125
2022-10-04 02:08:40,836 INFO Epoch = 4110 Total Loss = 138.14076232910156 content Loss = 14.564973831176758 style Loss = 12357.5791015625
2022-10-04 02:08:49,516 INFO Epoch = 4120 Total Loss = 131.81069946289062 content Loss = 14.58374309539795 style Loss = 11722.6953125
2022-10-04 02:08:58,188 INFO Epoch = 4130 Total Loss = 129.9725341796875 content Loss = 14.580732345581055 style Loss = 11539.181640625
2022-10-04 02:09:06,837 INFO Epoch = 4140 Total Loss = 129.9775848388672 content Loss = 14.575477600097656 style Loss = 11540.2109375
2022-10-04 02:09:15,622 INFO Epoch = 4150 Total Loss = 167.111083984375 content Loss = 14.551448822021484 style Loss = 15255.96484375
2022-10-04 02:09:24,596 INFO Epoch = 4160 Total Loss = 146.79888916015625 content Loss = 14.601947784423828 style Loss = 13219.6962890625
2022-10-04 02:09:33,284 INFO Epoch = 4170 Total Loss = 144.63534545898438 content Loss = 14.593927383422852 style Loss = 13004.1416015625
2022-10-04 02:09:41,916 INFO Epoch = 4180 Total Loss = 137.53135681152344 content Loss = 14.579684257507324 style Loss = 12295.1669921875
2022-10-04 02:09:50,578 INFO Epoch = 4190 Total Loss = 135.5077667236328 content Loss = 14.593023300170898 style Loss = 12091.4755859375
2022-10-04 02:09:59,207 INFO Epoch = 4200 Total Loss = 130.64019775390625 content Loss = 14.5808744430542 style Loss = 11605.931640625
2022-10-04 02:10:07,908 INFO Epoch = 4210 Total Loss = 129.4173126220703 content Loss = 14.595056533813477 style Loss = 11482.2265625
2022-10-04 02:10:16,798 INFO Epoch = 4220 Total Loss = 150.86561584472656 content Loss = 14.61345100402832 style Loss = 13625.216796875
2022-10-04 02:10:25,474 INFO Epoch = 4230 Total Loss = 142.44406127929688 content Loss = 14.576948165893555 style Loss = 12786.7109375
2022-10-04 02:10:34,145 INFO Epoch = 4240 Total Loss = 138.41162109375 content Loss = 14.603882789611816 style Loss = 12380.7744140625
2022-10-04 02:10:42,847 INFO Epoch = 4250 Total Loss = 132.19686889648438 content Loss = 14.581929206848145 style Loss = 11761.494140625
2022-10-04 02:10:51,537 INFO Epoch = 4260 Total Loss = 129.52041625976562 content Loss = 14.602500915527344 style Loss = 11491.791015625
2022-10-04 02:11:00,206 INFO Epoch = 4270 Total Loss = 229.25424194335938 content Loss = 14.646308898925781 style Loss = 21460.79296875
2022-10-04 02:11:09,031 INFO Epoch = 4280 Total Loss = 208.84674072265625 content Loss = 14.568948745727539 style Loss = 19427.779296875
2022-10-04 02:11:17,708 INFO Epoch = 4290 Total Loss = 149.63096618652344 content Loss = 14.5836820602417 style Loss = 13504.7294921875
2022-10-04 02:11:26,374 INFO Epoch = 4300 Total Loss = 225.14804077148438 content Loss = 14.655233383178711 style Loss = 21049.28125
2022-10-04 02:11:35,036 INFO Epoch = 4310 Total Loss = 141.12945556640625 content Loss = 14.58374309539795 style Loss = 12654.5712890625
2022-10-04 02:11:43,691 INFO Epoch = 4320 Total Loss = 141.14503479003906 content Loss = 14.575237274169922 style Loss = 12656.98046875
2022-10-04 02:11:52,321 INFO Epoch = 4330 Total Loss = 130.0059814453125 content Loss = 14.603851318359375 style Loss = 11540.2138671875
2022-10-04 02:12:00,974 INFO Epoch = 4340 Total Loss = 129.52371215820312 content Loss = 14.607680320739746 style Loss = 11491.6015625
2022-10-04 02:12:09,602 INFO Epoch = 4350 Total Loss = 127.9802474975586 content Loss = 14.60274887084961 style Loss = 11337.7509765625
2022-10-04 02:12:18,235 INFO Epoch = 4360 Total Loss = 127.59376525878906 content Loss = 14.609213829040527 style Loss = 11298.4541015625
2022-10-04 02:12:26,863 INFO Epoch = 4370 Total Loss = 151.5564727783203 content Loss = 14.584243774414062 style Loss = 13697.22265625
2022-10-04 02:12:35,661 INFO Epoch = 4380 Total Loss = 150.31524658203125 content Loss = 14.630170822143555 style Loss = 13568.505859375
2022-10-04 02:12:44,480 INFO Epoch = 4390 Total Loss = 129.92495727539062 content Loss = 14.609210968017578 style Loss = 11531.5751953125
2022-10-04 02:12:53,206 INFO Epoch = 4400 Total Loss = 131.96817016601562 content Loss = 14.606693267822266 style Loss = 11736.1484375
2022-10-04 02:13:01,979 INFO Epoch = 4410 Total Loss = 127.3923110961914 content Loss = 14.618778228759766 style Loss = 11277.3544921875
2022-10-04 02:13:10,702 INFO Epoch = 4420 Total Loss = 130.67584228515625 content Loss = 14.627012252807617 style Loss = 11604.8818359375
2022-10-04 02:13:19,368 INFO Epoch = 4430 Total Loss = 145.3986053466797 content Loss = 14.625434875488281 style Loss = 13077.3173828125
2022-10-04 02:13:27,983 INFO Epoch = 4440 Total Loss = 136.03150939941406 content Loss = 14.609062194824219 style Loss = 12142.244140625
2022-10-04 02:13:36,572 INFO Epoch = 4450 Total Loss = 130.41717529296875 content Loss = 14.629326820373535 style Loss = 11578.7861328125
2022-10-04 02:13:45,169 INFO Epoch = 4460 Total Loss = 129.0093994140625 content Loss = 14.624256134033203 style Loss = 11438.515625
2022-10-04 02:13:53,754 INFO Epoch = 4470 Total Loss = 127.34530639648438 content Loss = 14.628913879394531 style Loss = 11271.638671875
2022-10-04 02:14:02,339 INFO Epoch = 4480 Total Loss = 191.5877227783203 content Loss = 14.6704683303833 style Loss = 17691.724609375
2022-10-04 02:14:10,913 INFO Epoch = 4490 Total Loss = 185.7709197998047 content Loss = 14.583471298217773 style Loss = 17118.74609375
2022-10-04 02:14:19,507 INFO Epoch = 4500 Total Loss = 155.8396759033203 content Loss = 14.612887382507324 style Loss = 14122.677734375
2022-10-04 02:14:28,102 INFO Epoch = 4510 Total Loss = 142.0086669921875 content Loss = 14.62382698059082 style Loss = 12738.484375
2022-10-04 02:14:36,700 INFO Epoch = 4520 Total Loss = 130.7613525390625 content Loss = 14.62092399597168 style Loss = 11614.04296875
2022-10-04 02:14:45,292 INFO Epoch = 4530 Total Loss = 127.91477966308594 content Loss = 14.619608879089355 style Loss = 11329.517578125
2022-10-04 02:14:53,833 INFO Epoch = 4540 Total Loss = 135.58262634277344 content Loss = 14.610321044921875 style Loss = 12097.23046875
2022-10-04 02:15:02,391 INFO Epoch = 4550 Total Loss = 126.92699432373047 content Loss = 14.624486923217773 style Loss = 11230.25
2022-10-04 02:15:10,941 INFO Epoch = 4560 Total Loss = 126.67326354980469 content Loss = 14.637008666992188 style Loss = 11203.6259765625
2022-10-04 02:15:19,512 INFO Epoch = 4570 Total Loss = 127.22164154052734 content Loss = 14.626523971557617 style Loss = 11259.51171875
2022-10-04 02:15:28,031 INFO Epoch = 4580 Total Loss = 131.93043518066406 content Loss = 14.626936912536621 style Loss = 11730.3505859375
2022-10-04 02:15:36,606 INFO Epoch = 4590 Total Loss = 125.95979309082031 content Loss = 14.632675170898438 style Loss = 11132.7119140625
2022-10-04 02:15:45,141 INFO Epoch = 4600 Total Loss = 201.51791381835938 content Loss = 14.588974952697754 style Loss = 18692.89453125
2022-10-04 02:15:53,677 INFO Epoch = 4610 Total Loss = 241.7359619140625 content Loss = 14.677345275878906 style Loss = 22705.86328125
2022-10-04 02:16:02,243 INFO Epoch = 4620 Total Loss = 163.98907470703125 content Loss = 14.660192489624023 style Loss = 14932.8896484375
2022-10-04 02:16:10,789 INFO Epoch = 4630 Total Loss = 143.25160217285156 content Loss = 14.654451370239258 style Loss = 12859.716796875
2022-10-04 02:16:19,336 INFO Epoch = 4640 Total Loss = 131.06993103027344 content Loss = 14.645282745361328 style Loss = 11642.4638671875
2022-10-04 02:16:27,987 INFO Epoch = 4650 Total Loss = 127.63078308105469 content Loss = 14.637042999267578 style Loss = 11299.3740234375
2022-10-04 02:16:36,886 INFO Epoch = 4660 Total Loss = 127.9631118774414 content Loss = 14.635359764099121 style Loss = 11332.775390625
2022-10-04 02:16:46,186 INFO Epoch = 4670 Total Loss = 125.72109985351562 content Loss = 14.640645980834961 style Loss = 11108.044921875
2022-10-04 02:16:55,077 INFO Epoch = 4680 Total Loss = 126.61074829101562 content Loss = 14.652586936950684 style Loss = 11195.81640625
2022-10-04 02:17:04,002 INFO Epoch = 4690 Total Loss = 153.7954559326172 content Loss = 14.66534423828125 style Loss = 13913.0107421875
2022-10-04 02:17:12,724 INFO Epoch = 4700 Total Loss = 128.3199462890625 content Loss = 14.639446258544922 style Loss = 11368.0517578125
2022-10-04 02:17:21,439 INFO Epoch = 4710 Total Loss = 129.28717041015625 content Loss = 14.649749755859375 style Loss = 11463.7431640625
2022-10-04 02:17:30,555 INFO Epoch = 4720 Total Loss = 124.70055389404297 content Loss = 14.652437210083008 style Loss = 11004.8125
2022-10-04 02:17:39,453 INFO Epoch = 4730 Total Loss = 127.37294006347656 content Loss = 14.66133975982666 style Loss = 11271.1611328125
2022-10-04 02:17:48,070 INFO Epoch = 4740 Total Loss = 144.68646240234375 content Loss = 14.677035331726074 style Loss = 13000.943359375
2022-10-04 02:17:56,835 INFO Epoch = 4750 Total Loss = 130.439697265625 content Loss = 14.643889427185059 style Loss = 11579.580078125
2022-10-04 02:18:05,416 INFO Epoch = 4760 Total Loss = 136.36109924316406 content Loss = 14.654062271118164 style Loss = 12170.7041015625
2022-10-04 02:18:14,021 INFO Epoch = 4770 Total Loss = 195.2227783203125 content Loss = 14.700806617736816 style Loss = 18052.197265625
2022-10-04 02:18:22,593 INFO Epoch = 4780 Total Loss = 131.87022399902344 content Loss = 14.64138126373291 style Loss = 11722.8837890625
2022-10-04 02:18:31,168 INFO Epoch = 4790 Total Loss = 128.91305541992188 content Loss = 14.64622688293457 style Loss = 11426.6826171875
2022-10-04 02:18:39,797 INFO Epoch = 4800 Total Loss = 126.32585144042969 content Loss = 14.65381908416748 style Loss = 11167.2041015625
2022-10-04 02:18:48,432 INFO Epoch = 4810 Total Loss = 124.65365600585938 content Loss = 14.65998363494873 style Loss = 10999.3681640625
2022-10-04 02:18:57,083 INFO Epoch = 4820 Total Loss = 124.47193908691406 content Loss = 14.66028881072998 style Loss = 10981.1640625
2022-10-04 02:19:05,755 INFO Epoch = 4830 Total Loss = 250.08340454101562 content Loss = 14.603083610534668 style Loss = 23548.033203125
2022-10-04 02:19:14,382 INFO Epoch = 4840 Total Loss = 184.26219177246094 content Loss = 14.678030967712402 style Loss = 16958.416015625
2022-10-04 02:19:23,024 INFO Epoch = 4850 Total Loss = 149.56460571289062 content Loss = 14.689666748046875 style Loss = 13487.4931640625
2022-10-04 02:19:31,687 INFO Epoch = 4860 Total Loss = 130.24652099609375 content Loss = 14.670894622802734 style Loss = 11557.5634765625
2022-10-04 02:19:40,366 INFO Epoch = 4870 Total Loss = 127.7058334350586 content Loss = 14.658514976501465 style Loss = 11304.732421875
2022-10-04 02:19:49,233 INFO Epoch = 4880 Total Loss = 125.55452728271484 content Loss = 14.668720245361328 style Loss = 11088.580078125
2022-10-04 02:19:58,090 INFO Epoch = 4890 Total Loss = 124.09720611572266 content Loss = 14.671506881713867 style Loss = 10942.5693359375
2022-10-04 02:20:07,118 INFO Epoch = 4900 Total Loss = 133.59048461914062 content Loss = 14.665587425231934 style Loss = 11892.4892578125
2022-10-04 02:20:16,001 INFO Epoch = 4910 Total Loss = 124.02317810058594 content Loss = 14.680379867553711 style Loss = 10934.279296875
2022-10-04 02:20:24,948 INFO Epoch = 4920 Total Loss = 126.32832336425781 content Loss = 14.673673629760742 style Loss = 11165.46484375
2022-10-04 02:20:33,780 INFO Epoch = 4930 Total Loss = 125.03108978271484 content Loss = 14.68438720703125 style Loss = 11034.6708984375
2022-10-04 02:20:42,725 INFO Epoch = 4940 Total Loss = 123.98617553710938 content Loss = 14.6795072555542 style Loss = 10930.66796875
2022-10-04 02:20:51,639 INFO Epoch = 4950 Total Loss = 123.12703704833984 content Loss = 14.687317848205566 style Loss = 10843.97265625
2022-10-04 02:21:00,784 INFO Epoch = 4960 Total Loss = 249.05686950683594 content Loss = 14.74182415008545 style Loss = 23431.505859375
2022-10-04 02:21:10,067 INFO Epoch = 4970 Total Loss = 152.51129150390625 content Loss = 14.673738479614258 style Loss = 13783.755859375
2022-10-04 02:21:19,090 INFO Epoch = 4980 Total Loss = 142.28135681152344 content Loss = 14.671675682067871 style Loss = 12760.9677734375
2022-10-04 02:21:28,176 INFO Epoch = 4990 Total Loss = 147.459716796875 content Loss = 14.681116104125977 style Loss = 13277.8603515625
1508.06576/feature_maps.py
View file @ 12038f26
import torch
import torch.nn as NN
from logger import Logger
LOGGER = Logger().logger()
LOGGER.info("Started Feature Maps")
device=torch.device( "cuda" if (torch.cuda.is_available()) else 'cpu')
LOGGER.info("Running the model cuda_available = "+str(torch.cuda.is_available()))
#Author: @meetdoshi
class FeatureMaps:
class FeatureMaps():
def __init__(self,arch="vgg19"):
'''
Init function
@params
arch: str {vgg11,vgg13,vgg16,vgg19,vgg19bn}
'''
super()
try:
self.model = torch.hub.load('pytorch/vision:v0.10.0',arch,pretrained=True)
except:
LOGGER.error("Could not load model")
except Exception as e:
LOGGER.error("Could not load model" + str(e))
return
def get_model(self):
......@@ -33,7 +37,7 @@ class FeatureMaps:
LOGGER.error("Could not fetch layer "+str(layer))
return weights
def get_fmaps(self,img,layer=[0,5,10,19,28]):
def get_fmaps_content(self,img,layer=[21]):
'''
Function which will pass the image through the model and get the respective fmaps
@params
......@@ -49,6 +53,22 @@ class FeatureMaps:
layer_num+=1
return fmaps
def get_fmaps_style(self,img,layer=[0,5,10,19,28]):
'''
Function which will pass the image through the model and get the respective fmaps
@params
img: numpy image f64
layer: list
'''
fmaps = []
layer_num = 0
for layer_i in self.model.features:
img = layer_i(img)
if layer_num in layer:
fmaps.append(img)
layer_num+=1
return fmaps
'''
if __name__ == "__main__":
fmap = FeatureMaps()
model = fmap.get_model()
......@@ -57,3 +77,4 @@ if __name__ == "__main__":
print(len(weights))
for weight in weights:
print(type(weight),weight.shape)
'''
1508.06576/image2gif.py 0 → 100644
View file @ 12038f26
import imageio
import os
fnames = []
newNameFolder = 'content-4_2'
path = 'styled_images/'+newNameFolder
for img in os.listdir(path):
fnames.append(os.path.join(path+"/", img))
fnames.sort()
with imageio.get_writer('gifs/'+newNameFolder+".gif", mode='I',duration = 0.2) as writer:
for fname in fnames:
image = imageio.imread(fname)
writer.append_data(image)
1508.06576/logger.py
View file @ 12038f26
import logging
import os
from xml.dom.minidom import Identified
#Author: @meetdoshi
class Logger:
'''
......@@ -10,11 +11,12 @@ class Logger:
_formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
def __new__(cls,*args,**kwargs):
if not cls._instance:
os.system("rm -rf Logs/")
os.mkdir("Logs/")
logHandler = logging.FileHandler("Logs/style_transfer.log")
identifier = 'content-4_2'
if not os.path.isdir("Logs/"):
os.mkdir("Logs/")
logHandler = logging.FileHandler("Logs/style_transfer_"+identifier+".log")
logHandler.setFormatter(cls._formatter)
cls._logHandler = logging.getLogger("Logs/style_transfer.log")
cls._logHandler = logging.getLogger("Logs/style_transfer_"+identifier+".log")
cls._logHandler.setLevel(logging.INFO)
cls._logHandler.addHandler(logHandler)
cls._instance = super(Logger, cls).__new__(cls,*args,**kwargs)
......
1508.06576/loss.py
View file @ 12038f26
......@@ -14,12 +14,11 @@ class Loss:
Author: @meetdoshi
'''
l2_norm_sq = None
for i in range(len(F)):
try:
diff = F[i]-P[i]
l2_norm_sq = torch.mean(diff**2)
except Exception as e:
LOGGER.error("Error computing loss",e)
try:
diff = F-P
l2_norm_sq = torch.mean((diff)**2)
except Exception as e:
LOGGER.error("Error computing loss",e)
return l2_norm_sq
@staticmethod
......@@ -41,24 +40,33 @@ class Loss:
@params
Author: @soumyagupta
'''
for i in range(len(F)):
num_channels = F[i][1]
h = F[i][2]
w = F[i][3]
style_gram_matrix = Loss.gram_matrix(F[i])
target_gram_matrix = Loss.gram_matrix(A[i])
loss_s = torch.sum((style_gram_matrix-target_gram_matrix)**2)
constant = 1/(4.0*(num_channels**2)*((h*w)**2))
return constant*loss_s
num_channels = F.shape[1]
h = F.shape[2]
w = F.shape[3]
style_gram_matrix = Loss.gram_matrix(F)
target_gram_matrix = Loss.gram_matrix(A)
loss_s = torch.mean((style_gram_matrix-target_gram_matrix)**2)
#constant = 1/(4.0*(num_channels**2)*((h*w)**2))
return loss_s
@staticmethod
def total_loss(alpha,beta,cont_fmap_real,cont_fmap_noise,style_fmap_real,style_fmap_noise):
def total_loss(alpha,beta,cont_fmap_real,style_fmap_real,generated_fmaps_content,generated_fmaps_style):
'''
Function which computes total loss and returns it
@params
Author: @jiteshg
'''
content_loss = Loss.content_loss(cont_fmap_real, cont_fmap_noise)
style_loss = Loss.style_loss(style_fmap_real, style_fmap_noise)
loss_t = alpha*content_loss + beta*style_loss
return loss_t
\ No newline at end of file
loss_t = 0.0
a = 0.0
b = 0.0
for cont,gen_cont in zip(cont_fmap_real,generated_fmaps_content):
loss_cont = Loss.content_loss(cont,gen_cont)
a+= loss_cont
for gen_style,sty in zip(generated_fmaps_style,style_fmap_real):
loss_style = Loss.style_loss(sty,gen_style)
b+= loss_style
loss_t += alpha*a + beta*b
return loss_t,a,b
\ No newline at end of file
1508.06576/optimizer.py
View file @ 12038f26
from loss import Loss
from feature_maps import FeatureMaps
from feature_maps import LOGGER, FeatureMaps
import torch.optim as optim
from torchvision.utils import save_image
import matplotlib.pyplot as plt
import os
plt.ion()
class Optimizer:
@staticmethod
def gradient_descent(content_img, style_img, content_img_clone):
......@@ -14,24 +16,28 @@ class Optimizer:
content_img_clone: Copy of Original Image
Author: @gaurangathavale
'''
epoch = 1000
learning_rate = 0.001
alpha = 10
beta = 100
LOGGER.info("Running gradient descent with the following parameters")
epoch = 4000
learning_rate = 0.01
alpha = 1
beta = 0.01
identifier = "content-4_2"
os.mkdir("styled_images/"+identifier)
LOGGER.info(f"{epoch},{learning_rate},{alpha},{beta}")
optimizer=optim.Adam([content_img_clone],lr=learning_rate)
print(optimizer)
LOGGER.info("Optimizer = " + str(optimizer))
#fig = plt.figure()
#ax = fig.add_subplot(111)
feature_maps = FeatureMaps()
for e in range(epoch):
feature_maps = FeatureMaps()
content_fmaps = feature_maps.get_fmaps(content_img)
style_fmaps = feature_maps.get_fmaps(style_img)
# content_clone_fmaps = feature_maps.get_fmaps(content_img_clone)
content_white_noise_fmaps = feature_maps.get_fmaps(content_img, [21])
style_white_noise_fmaps = feature_maps.get_fmaps(style_img, [21])
content_fmaps = feature_maps.get_fmaps_content(content_img)
style_fmaps = feature_maps.get_fmaps_style(style_img)
generated_fmaps_content = feature_maps.get_fmaps_content(content_img_clone)
generated_fmaps_style = feature_maps.get_fmaps_style(content_img_clone)
total_loss = Loss.total_loss(alpha, beta, content_fmaps, content_white_noise_fmaps, style_fmaps, style_white_noise_fmaps)
total_loss,total_cont_loss,total_style_loss = Loss.total_loss(alpha, beta, content_fmaps, style_fmaps,generated_fmaps_content,generated_fmaps_style)
# clears x.grad for every parameter x in the optimizer.
# It’s important to call this before total_loss.backward(), otherwise it will accumulate the gradients from multiple passes.
......@@ -42,8 +48,9 @@ class Optimizer:
# Optimization Step / Update Rule
optimizer.step()
if(not (e%100)):
print(total_loss)
save_image(content_img_clone,"styled.png")
\ No newline at end of file
#plt.clf()
#plt.plot(content_img_clone)
if(e%10 == 0):
LOGGER.info(f"Epoch = {e} Total Loss = {total_loss} content Loss = {total_cont_loss} style Loss = {total_style_loss}")
name = "styled_images/"+identifier+"/styled_" + str(e) +".png"
save_image(content_img_clone,name)
\ No newline at end of file
1508.06576/preprocess.py
View file @ 12038f26
from os import device_encoding
from logger import Logger
from torch import transforms
import torch
import torchvision.transforms as transforms
from PIL import Image
import numpy as np
LOGGER = Logger().logger()
device=torch.device( "cuda" if (torch.cuda.is_available()) else 'cpu')
#Author: @meetdoshi
class Preprocessor:
@staticmethod
......@@ -32,9 +35,11 @@ class Preprocessor:
@params
img: 3d numpy array
'''
loader = transforms.Compose([transforms.ToTensor(),transforms.Resize([224,224]),transforms.Normalize(mean=[0.485, 0.456, 0.406],std=[0.229, 0.224, 0.225],),])
#loader = transforms.Compose([transforms.ToTensor(),transforms.Resize([224,224]),transforms.Normalize(mean=[0.485, 0.456, 0.406],std=[0.229, 0.224, 0.225],),])
loader = transforms.Compose([transforms.ToTensor(),transforms.Resize([224,224])])
img = loader(img).unsqueeze(0)
return img
#assert img.shape == (1,3,224,224)
return img.to(device,torch.float)
@staticmethod
......@@ -46,15 +51,12 @@ class Preprocessor:
'''
img = Preprocessor.load_image(path)
img = Preprocessor.reshape_img(img)
img = Preprocessor.subtract_mean(img)
#img = Preprocessor.subtract_mean(img)
return img
'''
if __name__=="__main__":
prec = Preprocessor()
img = np.zeros(shape=(4,4,3))
print(img.shape)
for i in range(img.shape[2]):
print(img[:,:,i])
img = prec.subtract_mean(img)
for i in range(img.shape[2]):
print(img[:,:,i])
img = prec.process('test/sem8.jpeg')
'''
1508.06576/requirements.txt 0 → 100644
View file @ 12038f26
matplotlib==3.5.1
numpy==1.21.5
Pillow==9.2.0
torch==1.12.1+cpu
torchvision==0.13.1+cpu
1508.06576/style_transfer.py
View file @ 12038f26
import os
import warnings
from optimizer import Optimizer
from loss import Loss
from preprocess import Preprocessor
......@@ -11,10 +12,10 @@ import argparse
import torchvision.models as models
import torch.optim as optim
from torchvision.utils import save_image
warnings.filterwarnings('ignore')
from logger import Logger
LOGGER = Logger().logger()
LOGGER.info("Started Style Transfer")
class StyleTransfer:
'''
Style Transfer Base Class
......@@ -32,12 +33,19 @@ class StyleTransfer:
device = torch.device( "cuda" if (torch.cuda.is_available()) else 'cpu')
content_img_path = 'Nikola-Tesla.jpg'
style_img_path = 'style-Image.jpg'
content_img_path = 'test/content.jpg'
style_img_path = 'test/style.jpg'
content_img = Preprocessor.process(content_img_path)
style_img = Preprocessor.process(style_img_path)
content_img_clone = content_img.clone().requires_grad_(True)
Optimizer.gradient_descent(content_img, style_img, content_img_clone)
\ No newline at end of file
Optimizer.gradient_descent(content_img, style_img, content_img_clone)
if __name__ == "__main__":
stf = StyleTransfer()
stf.pipeline()
\ No newline at end of file
1703.10593/logger.py 0 → 100644
View file @ 12038f26
import logging
import os
#Author: @meetdoshi
class Logger:
'''
Singleton logger class
'''
_instance = None
_logHandler = None
_formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
def __new__(cls,*args,**kwargs):
if not cls._instance:
os.system("rm -rf Logs/")
os.mkdir("Logs/")
logHandler = logging.FileHandler("Logs/style_transfer.log")
logHandler.setFormatter(cls._formatter)
cls._logHandler = logging.getLogger("Logs/style_transfer.log")
cls._logHandler.setLevel(logging.INFO)
cls._logHandler.addHandler(logHandler)
cls._instance = super(Logger, cls).__new__(cls,*args,**kwargs)
return cls._instance
def logger(self):
return self._logHandler
'''
#Demo use
if __name__ == "__main__":
a = Logger()
b = Logger()
print(a is b)
INFO = a.logger()
ERROR = b.logger()
INFO.info("TEST")
ERROR.info("ERROR")
'''
1703.10593/loss.py 0 → 100644
View file @ 12038f26
import numpy as np
import torch
from logger import Logger
LOGGER = Logger().logger()
class Loss:
@staticmethod
def adversarial_G():
'''
L_gan(G,Dy,X,Y) =
'''
\ No newline at end of file
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