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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
import torch.nn as NN
from logger import Logger from logger import Logger
LOGGER = Logger().logger() LOGGER = Logger().logger()
LOGGER.info("Started Feature Maps") 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 #Author: @meetdoshi
class FeatureMaps: class FeatureMaps():
def __init__(self,arch="vgg19"): def __init__(self,arch="vgg19"):
''' '''
Init function Init function
@params @params
arch: str {vgg11,vgg13,vgg16,vgg19,vgg19bn} arch: str {vgg11,vgg13,vgg16,vgg19,vgg19bn}
''' '''
super()
try: try:
self.model = torch.hub.load('pytorch/vision:v0.10.0',arch,pretrained=True) self.model = torch.hub.load('pytorch/vision:v0.10.0',arch,pretrained=True)
except: except Exception as e:
LOGGER.error("Could not load model") LOGGER.error("Could not load model" + str(e))
return return
def get_model(self): def get_model(self):
...@@ -33,7 +37,7 @@ class FeatureMaps: ...@@ -33,7 +37,7 @@ class FeatureMaps:
LOGGER.error("Could not fetch layer "+str(layer)) LOGGER.error("Could not fetch layer "+str(layer))
return weights 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 Function which will pass the image through the model and get the respective fmaps
@params @params
...@@ -49,6 +53,22 @@ class FeatureMaps: ...@@ -49,6 +53,22 @@ class FeatureMaps:
layer_num+=1 layer_num+=1
return fmaps 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__": if __name__ == "__main__":
fmap = FeatureMaps() fmap = FeatureMaps()
model = fmap.get_model() model = fmap.get_model()
...@@ -57,3 +77,4 @@ if __name__ == "__main__": ...@@ -57,3 +77,4 @@ if __name__ == "__main__":
print(len(weights)) print(len(weights))
for weight in weights: for weight in weights:
print(type(weight),weight.shape) 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 logging
import os import os
from xml.dom.minidom import Identified
#Author: @meetdoshi #Author: @meetdoshi
class Logger: class Logger:
''' '''
...@@ -10,11 +11,12 @@ class Logger: ...@@ -10,11 +11,12 @@ class Logger:
_formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s') _formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
def __new__(cls,*args,**kwargs): def __new__(cls,*args,**kwargs):
if not cls._instance: if not cls._instance:
os.system("rm -rf Logs/") identifier = 'content-4_2'
os.mkdir("Logs/") if not os.path.isdir("Logs/"):
logHandler = logging.FileHandler("Logs/style_transfer.log") os.mkdir("Logs/")
logHandler = logging.FileHandler("Logs/style_transfer_"+identifier+".log")
logHandler.setFormatter(cls._formatter) 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.setLevel(logging.INFO)
cls._logHandler.addHandler(logHandler) cls._logHandler.addHandler(logHandler)
cls._instance = super(Logger, cls).__new__(cls,*args,**kwargs) cls._instance = super(Logger, cls).__new__(cls,*args,**kwargs)
......
1508.06576/loss.py
View file @ 12038f26
...@@ -14,12 +14,11 @@ class Loss: ...@@ -14,12 +14,11 @@ class Loss:
Author: @meetdoshi Author: @meetdoshi
''' '''
l2_norm_sq = None l2_norm_sq = None
for i in range(len(F)): try:
try: diff = F-P
diff = F[i]-P[i] l2_norm_sq = torch.mean((diff)**2)
l2_norm_sq = torch.mean(diff**2) except Exception as e:
except Exception as e: LOGGER.error("Error computing loss",e)
LOGGER.error("Error computing loss",e)
return l2_norm_sq return l2_norm_sq
@staticmethod @staticmethod
...@@ -41,24 +40,33 @@ class Loss: ...@@ -41,24 +40,33 @@ class Loss:
@params @params
Author: @soumyagupta Author: @soumyagupta
''' '''
for i in range(len(F)): num_channels = F.shape[1]
num_channels = F[i][1] h = F.shape[2]
h = F[i][2] w = F.shape[3]
w = F[i][3] style_gram_matrix = Loss.gram_matrix(F)
style_gram_matrix = Loss.gram_matrix(F[i]) target_gram_matrix = Loss.gram_matrix(A)
target_gram_matrix = Loss.gram_matrix(A[i]) loss_s = torch.mean((style_gram_matrix-target_gram_matrix)**2)
loss_s = torch.sum((style_gram_matrix-target_gram_matrix)**2) #constant = 1/(4.0*(num_channels**2)*((h*w)**2))
constant = 1/(4.0*(num_channels**2)*((h*w)**2)) return loss_s
return constant*loss_s
@staticmethod @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 Function which computes total loss and returns it
@params @params
Author: @jiteshg Author: @jiteshg
''' '''
content_loss = Loss.content_loss(cont_fmap_real, cont_fmap_noise) loss_t = 0.0
style_loss = Loss.style_loss(style_fmap_real, style_fmap_noise) a = 0.0
loss_t = alpha*content_loss + beta*style_loss b = 0.0
return loss_t
\ No newline at end of file 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 loss import Loss
from feature_maps import FeatureMaps from feature_maps import LOGGER, FeatureMaps
import torch.optim as optim import torch.optim as optim
from torchvision.utils import save_image from torchvision.utils import save_image
import matplotlib.pyplot as plt
import os
plt.ion()
class Optimizer: class Optimizer:
@staticmethod @staticmethod
def gradient_descent(content_img, style_img, content_img_clone): def gradient_descent(content_img, style_img, content_img_clone):
...@@ -14,24 +16,28 @@ class Optimizer: ...@@ -14,24 +16,28 @@ class Optimizer:
content_img_clone: Copy of Original Image content_img_clone: Copy of Original Image
Author: @gaurangathavale Author: @gaurangathavale
''' '''
epoch = 1000 LOGGER.info("Running gradient descent with the following parameters")
learning_rate = 0.001 epoch = 4000
alpha = 10 learning_rate = 0.01
beta = 100 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) 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): for e in range(epoch):
feature_maps = FeatureMaps() content_fmaps = feature_maps.get_fmaps_content(content_img)
content_fmaps = feature_maps.get_fmaps(content_img) style_fmaps = feature_maps.get_fmaps_style(style_img)
style_fmaps = feature_maps.get_fmaps(style_img) generated_fmaps_content = feature_maps.get_fmaps_content(content_img_clone)
# content_clone_fmaps = feature_maps.get_fmaps(content_img_clone) generated_fmaps_style = feature_maps.get_fmaps_style(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])
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. # 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. # 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: ...@@ -42,8 +48,9 @@ class Optimizer:
# Optimization Step / Update Rule # Optimization Step / Update Rule
optimizer.step() optimizer.step()
#plt.clf()
if(not (e%100)): #plt.plot(content_img_clone)
print(total_loss) if(e%10 == 0):
LOGGER.info(f"Epoch = {e} Total Loss = {total_loss} content Loss = {total_cont_loss} style Loss = {total_style_loss}")
save_image(content_img_clone,"styled.png") name = "styled_images/"+identifier+"/styled_" + str(e) +".png"
\ No newline at end of file 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 logger import Logger
from torch import transforms import torch
import torchvision.transforms as transforms
from PIL import Image from PIL import Image
import numpy as np import numpy as np
LOGGER = Logger().logger() LOGGER = Logger().logger()
device=torch.device( "cuda" if (torch.cuda.is_available()) else 'cpu')
#Author: @meetdoshi #Author: @meetdoshi
class Preprocessor: class Preprocessor:
@staticmethod @staticmethod
...@@ -32,9 +35,11 @@ class Preprocessor: ...@@ -32,9 +35,11 @@ class Preprocessor:
@params @params
img: 3d numpy array 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) img = loader(img).unsqueeze(0)
return img #assert img.shape == (1,3,224,224)
return img.to(device,torch.float)
@staticmethod @staticmethod
...@@ -46,15 +51,12 @@ class Preprocessor: ...@@ -46,15 +51,12 @@ class Preprocessor:
''' '''
img = Preprocessor.load_image(path) img = Preprocessor.load_image(path)
img = Preprocessor.reshape_img(img) img = Preprocessor.reshape_img(img)
img = Preprocessor.subtract_mean(img) #img = Preprocessor.subtract_mean(img)
return img return img
'''
if __name__=="__main__": if __name__=="__main__":
prec = Preprocessor() prec = Preprocessor()
img = np.zeros(shape=(4,4,3)) img = np.zeros(shape=(4,4,3))
print(img.shape) img = prec.process('test/sem8.jpeg')
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])
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 os
import warnings
from optimizer import Optimizer from optimizer import Optimizer
from loss import Loss from loss import Loss
from preprocess import Preprocessor from preprocess import Preprocessor
...@@ -11,10 +12,10 @@ import argparse ...@@ -11,10 +12,10 @@ import argparse
import torchvision.models as models import torchvision.models as models
import torch.optim as optim import torch.optim as optim
from torchvision.utils import save_image from torchvision.utils import save_image
warnings.filterwarnings('ignore')
from logger import Logger from logger import Logger
LOGGER = Logger().logger() LOGGER = Logger().logger()
LOGGER.info("Started Style Transfer") LOGGER.info("Started Style Transfer")
class StyleTransfer: class StyleTransfer:
''' '''
Style Transfer Base Class Style Transfer Base Class
...@@ -32,12 +33,19 @@ class StyleTransfer: ...@@ -32,12 +33,19 @@ class StyleTransfer:
device = torch.device( "cuda" if (torch.cuda.is_available()) else 'cpu') device = torch.device( "cuda" if (torch.cuda.is_available()) else 'cpu')
content_img_path = 'Nikola-Tesla.jpg' content_img_path = 'test/content.jpg'
style_img_path = 'style-Image.jpg' style_img_path = 'test/style.jpg'
content_img = Preprocessor.process(content_img_path) content_img = Preprocessor.process(content_img_path)
style_img = Preprocessor.process(style_img_path) style_img = Preprocessor.process(style_img_path)
content_img_clone = content_img.clone().requires_grad_(True) content_img_clone = content_img.clone().requires_grad_(True)
Optimizer.gradient_descent(content_img, style_img, content_img_clone) Optimizer.gradient_descent(content_img, style_img, content_img_clone)
\ No newline at end of file
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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