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@ProGamerGov
Created October 24, 2017 06:29
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-image_size 512, -tv_weight 0
[libprotobuf WARNING google/protobuf/io/coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 1073741824 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING google/protobuf/io/coded_stream.cc:78] The total number of bytes read was 538683157
Successfully loaded models/VGG16_SOD_finetune.caffemodel
conv1_1: 64 3 3 3
conv1_2: 64 64 3 3
conv2_1: 128 64 3 3
conv2_2: 128 128 3 3
conv3_1: 256 128 3 3
conv3_2: 256 256 3 3
conv3_3: 256 256 3 3
conv4_1: 512 256 3 3
conv4_2: 512 512 3 3
conv4_3: 512 512 3 3
conv5_1: 512 512 3 3
conv5_2: 512 512 3 3
conv5_3: 512 512 3 3
fc6: 1 1 25088 4096
fc7: 1 1 4096 4096
fc8-SOD100: 1 1 4096 100
Setting up style layer 2 : relu1_1
Setting up style layer 7 : relu2_1
Setting up style layer 12 : relu3_1
Setting up style layer 19 : relu4_1
Setting up content layer 21 : relu4_2
Setting up style layer 26 : relu5_1
Capturing content targets
nn.Sequential {
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> (7) -> (8) -> output]
(1): nn.GPU(1) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> output]
(1): cudnn.SpatialConvolution(3 -> 64, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): nn.StyleLoss
}
(2): nn.GPU(2) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> output]
(1): cudnn.SpatialConvolution(64 -> 64, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): cudnn.SpatialMaxPooling(2x2, 2,2)
}
(3): nn.GPU(3) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> output]
(1): cudnn.SpatialConvolution(64 -> 128, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): nn.StyleLoss
(4): cudnn.SpatialConvolution(128 -> 128, 3x3, 1,1, 1,1)
(5): cudnn.ReLU
(6): cudnn.SpatialMaxPooling(2x2, 2,2)
}
(4): nn.GPU(4) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> output]
(1): cudnn.SpatialConvolution(128 -> 256, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): nn.StyleLoss
}
(5): nn.GPU(5) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> output]
(1): cudnn.SpatialConvolution(256 -> 256, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): cudnn.SpatialConvolution(256 -> 256, 3x3, 1,1, 1,1)
(4): cudnn.ReLU
(5): cudnn.SpatialMaxPooling(2x2, 2,2)
}
(6): nn.GPU(6) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> output]
(1): cudnn.SpatialConvolution(256 -> 512, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): nn.StyleLoss
(4): cudnn.SpatialConvolution(512 -> 512, 3x3, 1,1, 1,1)
(5): cudnn.ReLU
(6): nn.ContentLoss
}
(7): nn.GPU(7) @ nn.Sequential {
[input -> (1) -> (2) -> (3) -> (4) -> (5) -> output]
(1): cudnn.SpatialConvolution(512 -> 512, 3x3, 1,1, 1,1)
(2): cudnn.ReLU
(3): cudnn.SpatialMaxPooling(2x2, 2,2)
(4): cudnn.SpatialConvolution(512 -> 512, 3x3, 1,1, 1,1)
(5): cudnn.ReLU
}
(8): nn.GPU(8) @ nn.Sequential {
[input -> (1) -> output]
(1): nn.StyleLoss
}
}
gram updateOutput value: 0
gram updateOutput value 2: 63931088
gram updateOutput value: 0
gram updateOutput value 2: 920720896
gram updateOutput value: 0
gram updateOutput value 2: 372197152
gram updateOutput value: 0
gram updateOutput value 2: 38205304
gram updateOutput value: 0
gram updateOutput value 2: 1499164.875
Capturing style target 1
gram updateOutput value: 4.1074142456055
gram updateOutput value 2: 17971322
gram updateOutput value: 118.05953216553
gram updateOutput value 2: 327327616
gram updateOutput value: 95.450042724609
gram updateOutput value 2: 145223104
gram updateOutput value: 19.432222366333
gram updateOutput value 2: 16405109
gram updateOutput value: 3.0500583648682
gram updateOutput value 2: 1278367.125
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gram updateOutput value: 6.8129343986511
gram updateOutput value 2: 105558808
gram updateOutput value: 246.64805603027
gram updateOutput value 2: 1925916416
gram updateOutput value: 216.18815612793
gram updateOutput value 2: 877470336
gram updateOutput value: 47.680404663086
gram updateOutput value 2: 93552264
gram updateOutput value: 14.18642616272
gram updateOutput value 2: 6736320
y value: 82.659896850586
dy value: 0
Running optimization with ADAM
---
x1 value: -7.1907348632812
gram updateOutput value: 6.7818932533264
gram updateOutput value 2: 105558808
gram updateOutput value: 246.95088195801
gram updateOutput value 2: 1925916416
gram updateOutput value: 225.02751159668
gram updateOutput value 2: 877470336
gram updateOutput value: 47.58313369751
gram updateOutput value 2: 93552264
gram updateOutput value: 13.705079078674
gram updateOutput value 2: 6736320
gram 1 value: -1.9049767274737e-07
gram 2 value: -3.8099534549474e-07
gram 3 value: -3.8099534549474e-07
gram 1 value: 4.3528558535399e-07
gram 2 value: 8.7057117070799e-07
gram 3 value: 8.7057117070799e-07
gram 1 value: 5.9903804867645e-06
gram 2 value: 1.1980760973529e-05
gram 3 value: 1.1980760973529e-05
gram 1 value: 2.2959889633967e-07
gram 2 value: 4.5919779267933e-07
gram 3 value: 4.5919779267933e-07
gram 1 value: -1.3670438114843e-09
gram 2 value: -2.7340876229687e-09
gram 3 value: -2.7340876229687e-09
feval(x) grad value: -0.0015942031750455
---
StyleLoss:updateOutput input 1: 18.847623825073
StyleLoss:updateOutput output 1: 18.847623825073
StyleLoss:updateGradInput input 1: 18.847623825073
StyleLoss:updateOutput self.G 1: 105558808
StyleLoss:updateOutput self.G 2: 6.7818932533264
StyleLoss:updateGradInput self.gradInput 1: -2.6394277874431e-09
StyleLoss:updateGradInput self.gradInput 2: 0.00037283502751961
dG 1: -1.5157122106757e-05
dG 2: -9.7380827360216e-13
---
StyleLoss:updateOutput input 1: 168.56349182129
StyleLoss:updateOutput output 1: 168.56349182129
StyleLoss:updateGradInput input 1: 168.56349182129
StyleLoss:updateOutput self.G 1: 1925916416
StyleLoss:updateOutput self.G 2: 246.95088195801
StyleLoss:updateGradInput self.gradInput 1: 2.930061082651e-09
StyleLoss:updateGradInput self.gradInput 2: -1.4163530977385e-05
dG 1: 3.6967408959754e-05
dG 2: 4.7401475106179e-12
---
StyleLoss:updateOutput input 1: 232.46334838867
StyleLoss:updateOutput output 1: 232.46334838867
StyleLoss:updateGradInput input 1: 232.46334838867
StyleLoss:updateOutput self.G 1: 877470336
StyleLoss:updateOutput self.G 2: 225.02751159668
StyleLoss:updateGradInput self.gradInput 1: 5.5081098793153e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00031361999572255
dG 1: 0.00026975473156199
dG 2: 6.9178662798208e-11
---
StyleLoss:updateOutput input 1: 152.01593017578
StyleLoss:updateOutput output 1: 152.01593017578
StyleLoss:updateGradInput input 1: 152.01593017578
StyleLoss:updateOutput self.G 1: 93552264
StyleLoss:updateOutput self.G 2: 47.58313369751
StyleLoss:updateGradInput self.gradInput 1: 3.9566142362446e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00022891440312378
dG 1: -7.4203626354574e-07
dG 2: -3.7741999196067e-13
---
StyleLoss:updateOutput input 1: 82.659896850586
StyleLoss:updateOutput output 1: 82.659896850586
StyleLoss:updateGradInput input 1: 82.659896850586
StyleLoss:updateOutput self.G 1: 6736320
StyleLoss:updateOutput self.G 2: 13.705079078674
StyleLoss:updateGradInput self.gradInput 1: -1.0460101407261e-07
StyleLoss:updateGradInput self.gradInput 2: -0.00062760594300926
dG 1: -3.6723877201439e-06
dG 2: -7.4714930423103e-12
---
Iteration 1 / 2500
Content 1 loss: 4598131.640625
Style 1 loss: 21730.979919
Style 2 loss: 18174884.765625
Style 3 loss: 61770708.984375
Style 4 loss: 6159049.072266
Style 5 loss: 571164.276123
Total loss: 91295669.718933
optim value: -7.188117980957
---
x1 value: -7.188117980957
gram updateOutput value: 6.7818932533264
gram updateOutput value 2: 105899352
gram updateOutput value: 246.95088195801
gram updateOutput value 2: 1933717376
gram updateOutput value: 225.02751159668
gram updateOutput value 2: 863342912
gram updateOutput value: 47.58313369751
gram updateOutput value 2: 91500704
gram updateOutput value: 13.705079078674
gram updateOutput value 2: 6734720.5
gram 1 value: -5.1964406111438e-07
gram 2 value: -1.0392881222288e-06
gram 3 value: -1.0392881222288e-06
gram 1 value: -5.4789052228443e-07
gram 2 value: -1.0957810445689e-06
gram 3 value: -1.0957810445689e-06
gram 1 value: 2.7293406219542e-06
gram 2 value: 5.4586812439084e-06
gram 3 value: 5.4586812439084e-06
gram 1 value: 5.1377446652623e-07
gram 2 value: 1.0275489330525e-06
gram 3 value: 1.0275489330525e-06
gram 1 value: -6.4417937650774e-10
gram 2 value: -1.2883587530155e-09
gram 3 value: -1.2883587530155e-09
feval(x) grad value: 0.0014791858848184
---
StyleLoss:updateOutput input 1: 18.88685798645
StyleLoss:updateOutput output 1: 18.88685798645
StyleLoss:updateGradInput input 1: 18.88685798645
StyleLoss:updateOutput self.G 1: 105899352
StyleLoss:updateOutput self.G 2: 6.8037710189819
StyleLoss:updateGradInput self.gradInput 1: -1.4296617223408e-09
StyleLoss:updateGradInput self.gradInput 2: 0.00011784228263423
dG 1: -4.4741209421773e-06
dG 2: -2.8745191990587e-13
---
StyleLoss:updateOutput input 1: 168.99002075195
StyleLoss:updateOutput output 1: 168.99002075195
StyleLoss:updateGradInput input 1: 168.99002075195
StyleLoss:updateOutput self.G 1: 1933717376
StyleLoss:updateOutput self.G 2: 247.95115661621
StyleLoss:updateGradInput self.gradInput 1: 7.9938855535033e-09
StyleLoss:updateGradInput self.gradInput 2: -5.1635008276207e-05
dG 1: 0.00015906961925793
dG 2: 2.0396724240146e-11
---
StyleLoss:updateOutput input 1: 230.36422729492
StyleLoss:updateOutput output 1: 230.36422729492
StyleLoss:updateGradInput input 1: 230.36422729492
StyleLoss:updateOutput self.G 1: 863342912
StyleLoss:updateOutput self.G 2: 221.40446472168
StyleLoss:updateGradInput self.gradInput 1: 3.4475501564657e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00019469218386803
dG 1: 0.0001591895124875
dG 2: 4.0824180841392e-11
---
StyleLoss:updateOutput input 1: 149.82202148438
StyleLoss:updateOutput output 1: 149.82202148438
StyleLoss:updateGradInput input 1: 149.82202148438
StyleLoss:updateOutput self.G 1: 91500704
StyleLoss:updateOutput self.G 2: 46.539665222168
StyleLoss:updateGradInput self.gradInput 1: -7.5122436271613e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00037013867404312
dG 1: -8.7030812210287e-06
dG 2: -4.4266161916551e-12
---
StyleLoss:updateOutput input 1: 82.061813354492
StyleLoss:updateOutput output 1: 82.061813354492
StyleLoss:updateGradInput input 1: 82.061813354492
StyleLoss:updateOutput self.G 1: 6734720.5
StyleLoss:updateOutput self.G 2: 13.701824188232
StyleLoss:updateGradInput self.gradInput 1: -4.3685403738891e-07
StyleLoss:updateGradInput self.gradInput 2: -0.0026211242657155
dG 1: -3.6972214729758e-06
dG 2: -7.5220185982716e-12
---
Iteration 2 / 2500
Content 1 loss: 4506305.859375
Style 1 loss: 16246.170044
Style 2 loss: 12339707.519531
Style 3 loss: 34971550.781250
Style 4 loss: 3264162.597656
Style 5 loss: 268919.448853
Total loss: 55366892.376709
optim value: -7.1877503395081
---
x1 value: -7.1877503395081
gram updateOutput value: 6.8037710189819
gram updateOutput value 2: 107066744
gram updateOutput value: 247.95115661621
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gram updateOutput value: 221.40446472168
gram updateOutput value 2: 874999616
gram updateOutput value: 46.539665222168
gram updateOutput value 2: 94123768
gram updateOutput value: 13.701824188232
gram updateOutput value 2: 7271403.5
gram 1 value: 5.8886610077025e-07
gram 2 value: 1.1777322015405e-06
gram 3 value: 1.1777322015405e-06
gram 1 value: 7.250068989606e-08
gram 2 value: 1.4500137979212e-07
gram 3 value: 1.4500137979212e-07
gram 1 value: 4.2970054892066e-06
gram 2 value: 8.5940109784133e-06
gram 3 value: 8.5940109784133e-06
gram 1 value: 1.9100773442915e-06
gram 2 value: 3.820154688583e-06
gram 3 value: 3.820154688583e-06
gram 1 value: 2.5686084370591e-09
gram 2 value: 5.1372168741182e-09
gram 3 value: 5.1372168741182e-09
feval(x) grad value: -0.002862963359803
---
StyleLoss:updateOutput input 1: 18.999931335449
StyleLoss:updateOutput output 1: 18.999931335449
StyleLoss:updateGradInput input 1: 18.999931335449
StyleLoss:updateOutput self.G 1: 107066744
StyleLoss:updateOutput self.G 2: 6.87877368927
StyleLoss:updateGradInput self.gradInput 1: 6.5806995408479e-09
StyleLoss:updateGradInput self.gradInput 2: 0.00096541858511046
dG 1: 3.2148036552826e-05
dG 2: 2.0654315931179e-12
---
StyleLoss:updateOutput input 1: 170.2053527832
StyleLoss:updateOutput output 1: 170.2053527832
StyleLoss:updateGradInput input 1: 170.2053527832
StyleLoss:updateOutput self.G 1: 1959184256
StyleLoss:updateOutput self.G 2: 251.21664428711
StyleLoss:updateGradInput self.gradInput 1: 3.5303887813143e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00019884170615114
dG 1: 0.00055768934544176
dG 2: 7.1509784205226e-11
---
StyleLoss:updateOutput input 1: 231.78096008301
StyleLoss:updateOutput output 1: 231.78096008301
StyleLoss:updateGradInput input 1: 231.78096008301
StyleLoss:updateOutput self.G 1: 874999616
StyleLoss:updateOutput self.G 2: 224.39387512207
StyleLoss:updateGradInput self.gradInput 1: 7.2025549968657e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00037268933374435
dG 1: 0.00025041843764484
dG 2: 6.4219879414296e-11
---
StyleLoss:updateOutput input 1: 151.25479125977
StyleLoss:updateOutput output 1: 151.25479125977
StyleLoss:updateGradInput input 1: 151.25479125977
StyleLoss:updateOutput self.G 1: 94123768
StyleLoss:updateOutput self.G 2: 47.873821258545
StyleLoss:updateGradInput self.gradInput 1: 1.377973823935e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00017868015856948
dG 1: 1.4756598147869e-06
dG 2: 7.5055944532415e-13
---
StyleLoss:updateOutput input 1: 84.540489196777
StyleLoss:updateOutput output 1: 84.540489196777
StyleLoss:updateGradInput input 1: 84.540489196777
StyleLoss:updateOutput self.G 1: 7271403.5
StyleLoss:updateOutput self.G 2: 14.793710708618
StyleLoss:updateGradInput self.gradInput 1: 6.2912010889704e-07
StyleLoss:updateGradInput self.gradInput 2: 0.0037747207097709
dG 1: 4.6332193051057e-06
dG 2: 9.4263095593017e-12
---
Iteration 3 / 2500
Content 1 loss: 4697248.437500
Style 1 loss: 11644.593716
Style 2 loss: 8501633.056641
Style 3 loss: 20663040.527344
Style 4 loss: 2154235.290527
Style 5 loss: 168343.208313
Total loss: 36196145.114040
optim value: -7.1881861686707
---
x1 value: -7.1881861686707
gram updateOutput value: 6.87877368927
gram updateOutput value 2: 108040128
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gram 1 value: -3.2579899311713e-07
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gram 3 value: -6.5159798623426e-07
gram 1 value: 1.6677046232871e-07
gram 2 value: 3.3354092465743e-07
gram 3 value: 3.3354092465743e-07
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gram 2 value: 9.8726941359928e-06
gram 3 value: 9.8726941359928e-06
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gram 2 value: 6.2419871937891e-06
gram 3 value: 6.2419871937891e-06
gram 1 value: 5.394104718448e-09
gram 2 value: 1.0788209436896e-08
gram 3 value: 1.0788209436896e-08
feval(x) grad value: -0.0035857276525348
---
StyleLoss:updateOutput input 1: 19.095756530762
StyleLoss:updateOutput output 1: 19.095756530762
StyleLoss:updateGradInput input 1: 19.095756530762
StyleLoss:updateOutput self.G 1: 108040128
StyleLoss:updateOutput self.G 2: 6.9413118362427
StyleLoss:updateGradInput self.gradInput 1: 1.6149240167351e-08
StyleLoss:updateGradInput self.gradInput 2: 0.0014789697015658
dG 1: 6.2684091972187e-05
dG 2: 4.0272975926348e-12
---
StyleLoss:updateOutput input 1: 171.20048522949
StyleLoss:updateOutput output 1: 171.20048522949
StyleLoss:updateGradInput input 1: 171.20048522949
StyleLoss:updateOutput self.G 1: 1980075520
StyleLoss:updateOutput self.G 2: 253.89543151855
StyleLoss:updateGradInput self.gradInput 1: 6.5349638589396e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00028729540645145
dG 1: 0.00088469014735892
dG 2: 1.134395147262e-10
---
StyleLoss:updateOutput input 1: 231.75752258301
StyleLoss:updateOutput output 1: 231.75752258301
StyleLoss:updateGradInput input 1: 231.75752258301
StyleLoss:updateOutput self.G 1: 876909888
StyleLoss:updateOutput self.G 2: 224.88377380371
StyleLoss:updateGradInput self.gradInput 1: 1.0704803798944e-07
StyleLoss:updateGradInput self.gradInput 2: 0.00051755865570158
dG 1: 0.00026536892983131
dG 2: 6.805393054643e-11
---
StyleLoss:updateOutput input 1: 150.50416564941
StyleLoss:updateOutput output 1: 150.50416564941
StyleLoss:updateGradInput input 1: 150.50416564941
StyleLoss:updateOutput self.G 1: 94028656
StyleLoss:updateOutput self.G 2: 47.825458526611
StyleLoss:updateGradInput self.gradInput 1: 3.6960873472935e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00020960142137483
dG 1: 1.1066540537286e-06
dG 2: 5.6287342408562e-13
---
StyleLoss:updateOutput input 1: 81.235626220703
StyleLoss:updateOutput output 1: 81.235626220703
StyleLoss:updateGradInput input 1: 81.235626220703
StyleLoss:updateOutput self.G 1: 6783922.5
StyleLoss:updateOutput self.G 2: 13.801923751831
StyleLoss:updateGradInput self.gradInput 1: -4.451414383766e-07
StyleLoss:updateGradInput self.gradInput 2: -0.0026708489749581
dG 1: -2.9335053568502e-06
dG 2: -5.968230683967e-12
---
Iteration 4 / 2500
Content 1 loss: 4677410.546875
Style 1 loss: 8071.844101
Style 2 loss: 6197031.738281
Style 3 loss: 13751443.359375
Style 4 loss: 1775312.805176
Style 5 loss: 130430.374146
Total loss: 26539700.667953
optim value: -7.1873230934143
---
x1 value: -7.1873230934143
gram updateOutput value: 6.9413118362427
gram updateOutput value 2: 108524112
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gram updateOutput value 2: 1990671744
gram updateOutput value: 224.88377380371
gram updateOutput value 2: 874924288
gram updateOutput value: 47.825458526611
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gram updateOutput value 2: 6712294.5
gram 1 value: -4.0881880636334e-07
gram 2 value: -8.1763761272668e-07
gram 3 value: -8.1763761272668e-07
gram 1 value: 1.5072241410508e-07
gram 2 value: 3.0144482821015e-07
gram 3 value: 3.0144482821015e-07
gram 1 value: 4.921656454826e-06
gram 2 value: 9.843312909652e-06
gram 3 value: 9.843312909652e-06
gram 1 value: 3.7547520150838e-06
gram 2 value: 7.5095040301676e-06
gram 3 value: 7.5095040301676e-06
gram 1 value: 6.8158154675757e-09
gram 2 value: 1.3631630935151e-08
gram 3 value: 1.3631630935151e-08
feval(x) grad value: -0.0049882172606885
---
StyleLoss:updateOutput input 1: 19.136472702026
StyleLoss:updateOutput output 1: 19.136472702026
StyleLoss:updateGradInput input 1: 19.136472702026
StyleLoss:updateOutput self.G 1: 108524112
StyleLoss:updateOutput self.G 2: 6.9724063873291
StyleLoss:updateGradInput self.gradInput 1: 2.3925405656655e-08
StyleLoss:updateGradInput self.gradInput 2: 0.0017389332642779
dG 1: 7.7867080108263e-05
dG 2: 5.002767297646e-12
---
StyleLoss:updateOutput input 1: 171.67373657227
StyleLoss:updateOutput output 1: 171.67373657227
StyleLoss:updateGradInput input 1: 171.67373657227
StyleLoss:updateOutput self.G 1: 1990671744
StyleLoss:updateOutput self.G 2: 255.25415039062
StyleLoss:updateGradInput self.gradInput 1: 8.6621277262111e-08
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dG 2: 1.3470660698012e-10
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StyleLoss:updateOutput output 1: 231.19540405273
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StyleLoss:updateGradInput self.gradInput 2: 0.0006540163885802
dG 1: 0.00024982896866277
dG 2: 6.4068694793917e-11
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StyleLoss:updateOutput input 1: 149.5475769043
StyleLoss:updateOutput output 1: 149.5475769043
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StyleLoss:updateOutput self.G 2: 47.593772888184
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StyleLoss:updateGradInput self.gradInput 2: 0.00012798036914319
dG 1: -6.608671583308e-07
dG 2: -3.3613444059416e-13
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StyleLoss:updateOutput input 1: 80.604721069336
StyleLoss:updateOutput output 1: 80.604721069336
StyleLoss:updateGradInput input 1: 80.604721069336
StyleLoss:updateOutput self.G 1: 6712294.5
StyleLoss:updateOutput self.G 2: 13.656199455261
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StyleLoss:updateGradInput self.gradInput 2: -0.0037833435926586
dG 1: -4.0453019209963e-06
dG 2: -8.2301864975931e-12
---
Iteration 5 / 2500
Content 1 loss: 4699582.812500
Style 1 loss: 5605.540395
Style 2 loss: 4812728.027344
Style 3 loss: 10447829.589844
Style 4 loss: 1539817.932129
Style 5 loss: 109394.084930
Total loss: 21614957.987142
optim value: -7.1845517158508
---
x1 value: -7.1845517158508
gram updateOutput value: 6.9724063873291
gram updateOutput value 2: 108365504
gram updateOutput value: 255.25415039062
gram updateOutput value 2: 1988169728
gram updateOutput value: 224.37457275391
gram updateOutput value 2: 867544768
gram updateOutput value: 47.593772888184
gram updateOutput value 2: 92816320
gram updateOutput value: 13.656199455261
gram updateOutput value 2: 6899516.5
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gram 2 value: -2.0784330700963e-08
gram 3 value: -2.0784330700963e-08
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gram 2 value: 1.1146706668796e-08
gram 3 value: 1.1146706668796e-08
gram 1 value: 3.9263350117835e-06
gram 2 value: 7.852670023567e-06
gram 3 value: 7.852670023567e-06
gram 1 value: 3.6325591281638e-06
gram 2 value: 7.2651182563277e-06
gram 3 value: 7.2651182563277e-06
gram 1 value: 6.3079323986415e-09
gram 2 value: 1.2615864797283e-08
gram 3 value: 1.2615864797283e-08
feval(x) grad value: -0.005722691770643
---
StyleLoss:updateOutput input 1: 19.11371421814
StyleLoss:updateOutput output 1: 19.11371421814
StyleLoss:updateGradInput input 1: 19.11371421814
StyleLoss:updateOutput self.G 1: 108365504
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StyleLoss:updateGradInput self.gradInput 2: 0.0017118519172072
dG 1: 7.2891132731456e-05
dG 2: 4.6830755419391e-12
---
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StyleLoss:updateOutput output 1: 171.52792358398
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StyleLoss:updateOutput self.G 1: 1988169728
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StyleLoss:updateGradInput self.gradInput 2: 0.00055334635544568
dG 1: 0.001011383254081
dG 2: 1.2968476292841e-10
---
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StyleLoss:updateOutput output 1: 229.94090270996
StyleLoss:updateGradInput input 1: 229.94090270996
StyleLoss:updateOutput self.G 1: 867544768
StyleLoss:updateOutput self.G 2: 222.48210144043
StyleLoss:updateGradInput self.gradInput 1: 1.1805308730573e-07
StyleLoss:updateGradInput self.gradInput 2: 0.00065350445220247
dG 1: 0.00019207599689253
dG 2: 4.9257938006253e-11
---
StyleLoss:updateOutput input 1: 148.47862243652
StyleLoss:updateOutput output 1: 148.47862243652
StyleLoss:updateGradInput input 1: 148.47862243652
StyleLoss:updateOutput self.G 1: 92816320
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StyleLoss:updateGradInput self.gradInput 2: -0.00011453301704023
dG 1: -3.5978496271127e-06
dG 2: -1.8299610958505e-12
---
StyleLoss:updateOutput input 1: 81.671058654785
StyleLoss:updateOutput output 1: 81.671058654785
StyleLoss:updateGradInput input 1: 81.671058654785
StyleLoss:updateOutput self.G 1: 6899516.5
StyleLoss:updateOutput self.G 2: 14.03710269928
StyleLoss:updateGradInput self.gradInput 1: -1.7962834775176e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00010777710849652
dG 1: -1.1392432952562e-06
dG 2: -2.3177965623178e-12
---
Iteration 6 / 2500
Content 1 loss: 4732102.343750
Style 1 loss: 3964.513063
Style 2 loss: 3772222.045898
Style 3 loss: 8373677.490234
Style 4 loss: 1325103.881836
Style 5 loss: 91587.621689
Total loss: 18298657.896471
optim value: -7.1798849105835
---
x1 value: -7.1798849105835
gram updateOutput value: 6.962215423584
gram updateOutput value 2: 107578256
gram updateOutput value: 254.93328857422
gram updateOutput value 2: 1973523712
gram updateOutput value: 222.48210144043
gram updateOutput value 2: 853536128
gram updateOutput value: 47.208824157715
gram updateOutput value 2: 91307888
gram updateOutput value: 14.03710269928
gram updateOutput value 2: 6859257.5
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gram 3 value: -2.1910645386924e-07
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gram 2 value: -7.1582945793125e-07
gram 3 value: -7.1582945793125e-07
gram 1 value: 1.8661066860659e-06
gram 2 value: 3.7322133721318e-06
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gram 1 value: 2.8156157441117e-06
gram 2 value: 5.6312314882234e-06
gram 3 value: 5.6312314882234e-06
gram 1 value: 3.92889853984e-09
gram 2 value: 7.85779707968e-09
gram 3 value: 7.85779707968e-09
feval(x) grad value: -0.0021715813782066
---
StyleLoss:updateOutput input 1: 19.034032821655
StyleLoss:updateOutput output 1: 19.034032821655
StyleLoss:updateGradInput input 1: 19.034032821655
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StyleLoss:updateGradInput self.gradInput 2: 0.0011862829560414
dG 1: 4.8194426199188e-05
dG 2: 3.0963732012418e-12
---
StyleLoss:updateOutput input 1: 170.8278503418
StyleLoss:updateOutput output 1: 170.8278503418
StyleLoss:updateGradInput input 1: 170.8278503418
StyleLoss:updateOutput self.G 1: 1973523712
StyleLoss:updateOutput self.G 2: 253.05529785156
StyleLoss:updateGradInput self.gradInput 1: 8.7801588222192e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00048579135909677
dG 1: 0.00078213377855718
dG 2: 1.0028922137195e-10
---
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StyleLoss:updateOutput output 1: 227.8352355957
StyleLoss:updateGradInput input 1: 227.8352355957
StyleLoss:updateOutput self.G 1: 853536128
StyleLoss:updateOutput self.G 2: 218.88961791992
StyleLoss:updateGradInput self.gradInput 1: 6.7786764645916e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00041526419227012
dG 1: 8.2441278209444e-05
dG 2: 2.1142084610792e-11
---
StyleLoss:updateOutput input 1: 146.94233703613
StyleLoss:updateOutput output 1: 146.94233703613
StyleLoss:updateGradInput input 1: 146.94233703613
StyleLoss:updateOutput self.G 1: 91307888
StyleLoss:updateOutput self.G 2: 46.441589355469
StyleLoss:updateGradInput self.gradInput 1: -1.1321299098199e-07
StyleLoss:updateGradInput self.gradInput 2: -0.00080037268344313
dG 1: -9.4513870863011e-06
dG 2: -4.8072236295826e-12
---
StyleLoss:updateOutput input 1: 81.471115112305
StyleLoss:updateOutput output 1: 81.471115112305
StyleLoss:updateGradInput input 1: 81.471115112305
StyleLoss:updateOutput self.G 1: 6859257.5
StyleLoss:updateOutput self.G 2: 13.95519733429
StyleLoss:updateGradInput self.gradInput 1: -2.1378673409345e-07
StyleLoss:updateGradInput self.gradInput 2: -0.0012827204773203
dG 1: -1.7641435761107e-06
dG 2: -3.5891597853499e-12
---
Iteration 7 / 2500
Content 1 loss: 4695026.953125
Style 1 loss: 2846.384525
Style 2 loss: 2830975.341797
Style 3 loss: 6777261.474609
Style 4 loss: 1162623.962402
Style 5 loss: 79325.237274
Total loss: 15548059.353733
optim value: -7.1753406524658
---
x1 value: -7.1753406524658
gram updateOutput value: 6.9116363525391
gram updateOutput value 2: 106563016
gram updateOutput value: 253.05529785156
gram updateOutput value 2: 1955336320
gram updateOutput value: 218.88961791992
gram updateOutput value 2: 843803904
gram updateOutput value: 46.441589355469
gram updateOutput value 2: 91153640
gram updateOutput value: 13.95519733429
gram updateOutput value 2: 6952290
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gram 2 value: 9.7139427168713e-08
gram 3 value: 9.7139427168713e-08
gram 1 value: -4.2541049083411e-07
gram 2 value: -8.5082098166822e-07
gram 3 value: -8.5082098166822e-07
gram 1 value: 3.6269491943131e-07
gram 2 value: 7.2538983886261e-07
gram 3 value: 7.2538983886261e-07
gram 1 value: 1.8001302350967e-06
gram 2 value: 3.6002604701935e-06
gram 3 value: 3.6002604701935e-06
gram 1 value: 8.9459756269505e-10
gram 2 value: 1.7891951253901e-09
gram 3 value: 1.7891951253901e-09
feval(x) grad value: 0.00051772099686787
---
StyleLoss:updateOutput input 1: 18.928575515747
StyleLoss:updateOutput output 1: 18.928575515747
StyleLoss:updateGradInput input 1: 18.928575515747
StyleLoss:updateOutput self.G 1: 106563016
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StyleLoss:updateGradInput self.gradInput 2: 0.00063774560112506
dG 1: 1.6345642507076e-05
dG 2: 1.0501673315677e-12
---
StyleLoss:updateOutput input 1: 169.93238830566
StyleLoss:updateOutput output 1: 169.93238830566
StyleLoss:updateGradInput input 1: 169.93238830566
StyleLoss:updateOutput self.G 1: 1955336320
StyleLoss:updateOutput self.G 2: 250.72323608398
StyleLoss:updateGradInput self.gradInput 1: 7.0446823485781e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00038491364102811
dG 1: 0.00049745984142646
dG 2: 6.3786850801328e-11
---
StyleLoss:updateOutput input 1: 226.32284545898
StyleLoss:updateOutput output 1: 226.32284545898
StyleLoss:updateGradInput input 1: 226.32284545898
StyleLoss:updateOutput self.G 1: 843803904
StyleLoss:updateOutput self.G 2: 216.39373779297
StyleLoss:updateGradInput self.gradInput 1: 1.5570428502087e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00013739110727329
dG 1: 6.2735584833717e-06
dG 2: 1.6088544342249e-12
---
StyleLoss:updateOutput input 1: 146.60005187988
StyleLoss:updateOutput output 1: 146.60005187988
StyleLoss:updateGradInput input 1: 146.60005187988
StyleLoss:updateOutput self.G 1: 91153640
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StyleLoss:updateGradInput self.gradInput 1: -1.5216510007576e-07
StyleLoss:updateGradInput self.gradInput 2: -0.00099787302315235
dG 1: -1.0049950105895e-05
dG 2: -5.11166933434e-12
---
StyleLoss:updateOutput input 1: 82.086059570312
StyleLoss:updateOutput output 1: 82.086059570312
StyleLoss:updateGradInput input 1: 82.086059570312
StyleLoss:updateOutput self.G 1: 6952290
StyleLoss:updateOutput self.G 2: 14.144474029541
StyleLoss:updateGradInput self.gradInput 1: 9.951649104778e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00059709866764024
dG 1: -3.2008418315854e-07
dG 2: -6.5121297026724e-13
---
Iteration 8 / 2500
Content 1 loss: 4719653.515625
Style 1 loss: 2118.537068
Style 2 loss: 2085873.779297
Style 3 loss: 5590671.020508
Style 4 loss: 1027168.212891
Style 5 loss: 72663.425446
Total loss: 13498148.490834
optim value: -7.170693397522
---
x1 value: -7.170693397522
gram updateOutput value: 6.8464097976685
gram updateOutput value 2: 105627520
gram updateOutput value: 250.72323608398
gram updateOutput value 2: 1939620352
gram updateOutput value: 216.39373779297
gram updateOutput value 2: 839988032
gram updateOutput value: 46.363136291504
gram updateOutput value 2: 92119448
gram updateOutput value: 14.144474029541
gram updateOutput value 2: 7044466.5
gram 1 value: 2.0306012515903e-07
gram 2 value: 4.0612025031805e-07
gram 3 value: 4.0612025031805e-07
gram 1 value: -2.308489825964e-07
gram 2 value: -4.616979651928e-07
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gram 1 value: -1.8606811647004e-09
gram 2 value: -3.7213623294008e-09
gram 3 value: -3.7213623294008e-09
feval(x) grad value: 0.0018068107310683
---
StyleLoss:updateOutput input 1: 18.826789855957
StyleLoss:updateOutput output 1: 18.826789855957
StyleLoss:updateGradInput input 1: 18.826789855957
StyleLoss:updateOutput self.G 1: 105627520
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StyleLoss:updateGradInput self.gradInput 2: 0.00033379756496288
dG 1: -1.3001331353735e-05
dG 2: -8.3530328921083e-13
---
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StyleLoss:updateOutput output 1: 169.11643981934
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StyleLoss:updateOutput self.G 1: 1939620352
StyleLoss:updateOutput self.G 2: 248.70808410645
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StyleLoss:updateGradInput self.gradInput 2: 0.00024423043942079
dG 1: 0.00025146701955236
dG 2: 3.2244394654324e-11
---
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StyleLoss:updateOutput output 1: 225.61665344238
StyleLoss:updateGradInput input 1: 225.61665344238
StyleLoss:updateOutput self.G 1: 839988032
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StyleLoss:updateGradInput self.gradInput 2: -3.9587954233866e-05
dG 1: -2.3590866476297e-05
dG 2: -6.0498854190238e-12
---
StyleLoss:updateOutput input 1: 147.23652648926
StyleLoss:updateOutput output 1: 147.23652648926
StyleLoss:updateGradInput input 1: 147.23652648926
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StyleLoss:updateGradInput self.gradInput 2: -0.00058696779888123
dG 1: -6.3020784182299e-06
dG 2: -3.2054029569517e-12
---
StyleLoss:updateOutput input 1: 82.66943359375
StyleLoss:updateOutput output 1: 82.66943359375
StyleLoss:updateGradInput input 1: 82.66943359375
StyleLoss:updateOutput self.G 1: 7044466.5
StyleLoss:updateOutput self.G 2: 14.332003593445
StyleLoss:updateGradInput self.gradInput 1: 4.2790225052158e-07
StyleLoss:updateGradInput self.gradInput 2: 0.0025674137286842
dG 1: 1.1106809552075e-06
dG 2: 2.2596863616386e-12
---
Iteration 9 / 2500
Content 1 loss: 4774800.781250
Style 1 loss: 1670.226574
Style 2 loss: 1581988.586426
Style 3 loss: 4698600.952148
Style 4 loss: 921810.058594
Style 5 loss: 68244.243622
Total loss: 12047114.848614
optim value: -7.165810585022
---
x1 value: -7.165810585022
gram updateOutput value: 6.7863073348999
gram updateOutput value 2: 104950968
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gram updateOutput value 2: 1929223168
gram updateOutput value: 215.41511535645
gram updateOutput value 2: 838694464
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gram updateOutput value 2: 92852856
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gram updateOutput value 2: 6943226
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gram 2 value: -7.640376331608e-09
gram 3 value: -7.640376331608e-09
feval(x) grad value: 0.0039610834792256
---
StyleLoss:updateOutput input 1: 18.74866104126
StyleLoss:updateOutput output 1: 18.74866104126
StyleLoss:updateGradInput input 1: 18.74866104126
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dG 2: -2.1989207329987e-12
---
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StyleLoss:updateOutput output 1: 168.52885437012
StyleLoss:updateGradInput input 1: 168.52885437012
StyleLoss:updateOutput self.G 1: 1929223168
StyleLoss:updateOutput self.G 2: 247.3748626709
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StyleLoss:updateGradInput self.gradInput 2: 4.2959909478668e-05
dG 1: 8.8723114458844e-05
dG 2: 1.1376531661167e-11
---
StyleLoss:updateOutput input 1: 225.2508392334
StyleLoss:updateOutput output 1: 225.2508392334
StyleLoss:updateGradInput input 1: 225.2508392334
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dG 2: -8.6459919085291e-12
---
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StyleLoss:updateOutput output 1: 147.69555664062
StyleLoss:updateGradInput input 1: 147.69555664062
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StyleLoss:updateGradInput self.gradInput 2: -0.00021034613018855
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dG 2: -1.7578658797687e-12
---
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StyleLoss:updateOutput output 1: 82.045249938965
StyleLoss:updateGradInput input 1: 82.045249938965
StyleLoss:updateOutput self.G 1: 6943226
StyleLoss:updateOutput self.G 2: 14.12603187561
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StyleLoss:updateGradInput self.gradInput 2: -0.00056146836141124
dG 1: -4.6077047954896e-07
dG 2: -9.3744022960918e-13
---
Iteration 10 / 2500
Content 1 loss: 4786514.843750
Style 1 loss: 1393.290997
Style 2 loss: 1262601.654053
Style 3 loss: 4038058.593750
Style 4 loss: 846134.674072
Style 5 loss: 61877.677917
Total loss: 10996580.734539
optim value: -7.1622176170349
---
x1 value: -7.1622176170349
gram updateOutput value: 6.7428398132324
gram updateOutput value 2: 104689776
gram updateOutput value: 247.3748626709
gram updateOutput value 2: 1926613888
gram updateOutput value: 215.08343505859
gram updateOutput value 2: 842267456
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gram updateOutput value 2: 93772696
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gram updateOutput value 2: 6996806
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gram 3 value: 1.0854139986805e-07
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gram 2 value: 1.8814218094576e-07
gram 3 value: 1.8814218094576e-07
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gram 3 value: 1.4261111402902e-07
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gram 2 value: 5.3153434009801e-07
gram 3 value: 5.3153434009801e-07
gram 1 value: -4.5689505512314e-09
gram 2 value: -9.1379011024628e-09
gram 3 value: -9.1379011024628e-09
feval(x) grad value: 0.0025579901412129
---
StyleLoss:updateOutput input 1: 18.706491470337
StyleLoss:updateOutput output 1: 18.706491470337
StyleLoss:updateGradInput input 1: 18.706491470337
StyleLoss:updateOutput self.G 1: 104689776
StyleLoss:updateOutput self.G 2: 6.7260599136353
StyleLoss:updateGradInput self.gradInput 1: -3.0754456759041e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00044978770893067
dG 1: -4.2419513192726e-05
dG 2: -2.7253490263168e-12
---
StyleLoss:updateOutput input 1: 168.28108215332
StyleLoss:updateOutput output 1: 168.28108215332
StyleLoss:updateGradInput input 1: 168.28108215332
StyleLoss:updateOutput self.G 1: 1926613888
StyleLoss:updateOutput self.G 2: 247.04028320312
StyleLoss:updateGradInput self.gradInput 1: 1.721021014589e-08
StyleLoss:updateGradInput self.gradInput 2: 7.806235953467e-05
dG 1: 4.7882673243294e-05
dG 2: 6.1397614423142e-12
---
StyleLoss:updateOutput input 1: 225.54531860352
StyleLoss:updateOutput output 1: 225.54531860352
StyleLoss:updateGradInput input 1: 225.54531860352
StyleLoss:updateOutput self.G 1: 842267456
StyleLoss:updateOutput self.G 2: 215.99967956543
StyleLoss:updateGradInput self.gradInput 1: 4.447527235385e-09
StyleLoss:updateGradInput self.gradInput 2: 4.4604503273149e-06
dG 1: -5.7515262597008e-06
dG 2: -1.4749792099505e-12
---
StyleLoss:updateOutput input 1: 148.2559967041
StyleLoss:updateOutput output 1: 148.2559967041
StyleLoss:updateGradInput input 1: 148.2559967041
StyleLoss:updateOutput self.G 1: 93772696
StyleLoss:updateOutput self.G 2: 47.695259094238
StyleLoss:updateGradInput self.gradInput 1: 4.3676973149331e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00030563032487407
dG 1: 1.1331661653458e-07
dG 2: 5.7635726703406e-14
---
StyleLoss:updateOutput input 1: 82.283187866211
StyleLoss:updateOutput output 1: 82.283187866211
StyleLoss:updateGradInput input 1: 82.283187866211
StyleLoss:updateOutput self.G 1: 6996806
StyleLoss:updateOutput self.G 2: 14.235036849976
StyleLoss:updateGradInput self.gradInput 1: 1.3963432365927e-07
StyleLoss:updateGradInput self.gradInput 2: 0.00083780591376126
dG 1: 3.7088219073667e-07
dG 2: 7.5456183185399e-13
---
Iteration 11 / 2500
Content 1 loss: 4837343.750000
Style 1 loss: 1172.249794
Style 2 loss: 1046074.127197
Style 3 loss: 3495635.742188
Style 4 loss: 777816.284180
Style 5 loss: 57016.473770
Total loss: 10215058.627129
optim value: -7.1608052253723
---
x1 value: -7.1608052253723
gram updateOutput value: 6.7260599136353
gram updateOutput value 2: 104638632
gram updateOutput value: 247.04028320312
gram updateOutput value 2: 1927172480
gram updateOutput value: 215.99967956543
gram updateOutput value 2: 844052608
gram updateOutput value: 47.695259094238
gram updateOutput value 2: 93798096
gram updateOutput value: 14.235036849976
gram updateOutput value 2: 6936962.5
gram 1 value: -7.0019389397658e-08
gram 2 value: -1.4003877879532e-07
gram 3 value: -1.4003877879532e-07
gram 1 value: 6.0652169509012e-08
gram 2 value: 1.2130433901802e-07
gram 3 value: 1.2130433901802e-07
gram 1 value: 2.8824140940742e-07
gram 2 value: 5.7648281881484e-07
gram 3 value: 5.7648281881484e-07
gram 1 value: 3.140386013456e-07
gram 2 value: 6.280772026912e-07
gram 3 value: 6.280772026912e-07
gram 1 value: -4.6954942156674e-09
gram 2 value: -9.3909884313348e-09
gram 3 value: -9.3909884313348e-09
feval(x) grad value: 0.0028872373513877
---
StyleLoss:updateOutput input 1: 18.686204910278
StyleLoss:updateOutput output 1: 18.686204910278
StyleLoss:updateGradInput input 1: 18.686204910278
StyleLoss:updateOutput self.G 1: 104638632
StyleLoss:updateOutput self.G 2: 6.7227735519409
StyleLoss:updateGradInput self.gradInput 1: -3.4029202566899e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00046709270100109
dG 1: -4.4023905502399e-05
dG 2: -2.8284273794615e-12
---
StyleLoss:updateOutput input 1: 168.18537902832
StyleLoss:updateOutput output 1: 168.18537902832
StyleLoss:updateGradInput input 1: 168.18537902832
StyleLoss:updateOutput self.G 1: 1927172480
StyleLoss:updateOutput self.G 2: 247.11193847656
StyleLoss:updateGradInput self.gradInput 1: 2.2439218483328e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00010805366764544
dG 1: 5.6625583965797e-05
dG 2: 7.2608221518555e-12
---
StyleLoss:updateOutput input 1: 225.60841369629
StyleLoss:updateOutput output 1: 225.60841369629
StyleLoss:updateGradInput input 1: 225.60841369629
StyleLoss:updateOutput self.G 1: 844052608
StyleLoss:updateOutput self.G 2: 216.45747375488
StyleLoss:updateGradInput self.gradInput 1: 1.9912004489697e-08
StyleLoss:updateGradInput self.gradInput 2: 0.0001001393320621
dG 1: 8.2187834777869e-06
dG 2: 2.1077085389509e-12
---
StyleLoss:updateOutput input 1: 148.06065368652
StyleLoss:updateOutput output 1: 148.06065368652
StyleLoss:updateGradInput input 1: 148.06065368652
StyleLoss:updateOutput self.G 1: 93798096
StyleLoss:updateOutput self.G 2: 47.708183288574
StyleLoss:updateGradInput self.gradInput 1: 3.0330589595451e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00018968140648212
dG 1: 2.118736972534e-07
dG 2: 1.0776455953727e-13
---
StyleLoss:updateOutput input 1: 81.801795959473
StyleLoss:updateOutput output 1: 81.801795959473
StyleLoss:updateGradInput input 1: 81.801795959473
StyleLoss:updateOutput self.G 1: 6936962.5
StyleLoss:updateOutput self.G 2: 14.113283157349
StyleLoss:updateGradInput self.gradInput 1: -1.9332118483817e-07
StyleLoss:updateGradInput self.gradInput 2: -0.0011599272256717
dG 1: -5.5803371878937e-07
dG 2: -1.1353226301788e-12
---
Iteration 12 / 2500
Content 1 loss: 4845891.015625
Style 1 loss: 999.856621
Style 2 loss: 886620.391846
Style 3 loss: 3051742.675781
Style 4 loss: 719380.828857
Style 5 loss: 53442.712784
Total loss: 9558077.481514
optim value: -7.1624493598938
---
x1 value: -7.1624493598938
gram updateOutput value: 6.7227735519409
gram updateOutput value 2: 104687280
gram updateOutput value: 247.11193847656
gram updateOutput value 2: 1928859904
gram updateOutput value: 216.45747375488
gram updateOutput value 2: 845845440
gram updateOutput value: 47.708183288574
gram updateOutput value 2: 93943656
gram updateOutput value: 14.113283157349
gram updateOutput value 2: 6939956
gram 1 value: -5.0989569899684e-08
gram 2 value: -1.0197913979937e-07
gram 3 value: -1.0197913979937e-07
gram 1 value: 7.3508815034984e-08
gram 2 value: 1.4701763006997e-07
gram 3 value: 1.4701763006997e-07
gram 1 value: 5.0383295047141e-07
gram 2 value: 1.0076659009428e-06
gram 3 value: 1.0076659009428e-06
gram 1 value: 4.112511362564e-07
gram 2 value: 8.2250227251279e-07
gram 3 value: 8.2250227251279e-07
gram 1 value: -4.5227643852286e-09
gram 2 value: -9.0455287704572e-09
gram 3 value: -9.0455287704572e-09
feval(x) grad value: 0.002015987643972
---
StyleLoss:updateOutput input 1: 18.675819396973
StyleLoss:updateOutput output 1: 18.675819396973
StyleLoss:updateGradInput input 1: 18.675819396973
StyleLoss:updateOutput self.G 1: 104687280
StyleLoss:updateOutput self.G 2: 6.7258973121643
StyleLoss:updateGradInput self.gradInput 1: -3.5203338910605e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00058369478210807
dG 1: -4.24982754339e-05
dG 2: -2.7304089978558e-12
---
StyleLoss:updateOutput input 1: 168.13591003418
StyleLoss:updateOutput output 1: 168.13591003418
StyleLoss:updateGradInput input 1: 168.13591003418
StyleLoss:updateOutput self.G 1: 1928859904
StyleLoss:updateOutput self.G 2: 247.32830810547
StyleLoss:updateGradInput self.gradInput 1: 3.1703478953204e-08
StyleLoss:updateGradInput self.gradInput 2: 0.0001501280348748
dG 1: 8.3036553405691e-05
dG 2: 1.0647371873063e-11
---
StyleLoss:updateOutput input 1: 225.68511962891
StyleLoss:updateOutput output 1: 225.68511962891
StyleLoss:updateGradInput input 1: 225.68511962891
StyleLoss:updateOutput self.G 1: 845845440
StyleLoss:updateOutput self.G 2: 216.9172668457
StyleLoss:updateGradInput self.gradInput 1: 3.8006945146662e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00020677136490121
dG 1: 2.2250385882217e-05
dG 2: 5.7061178698747e-12
---
StyleLoss:updateOutput input 1: 147.96473693848
StyleLoss:updateOutput output 1: 147.96473693848
StyleLoss:updateGradInput input 1: 147.96473693848
StyleLoss:updateOutput self.G 1: 93943656
StyleLoss:updateOutput self.G 2: 47.782230377197
StyleLoss:updateGradInput self.gradInput 1: 3.9610888791231e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00018257660849486
dG 1: 7.7680175536443e-07
dG 2: 3.951017301957e-13
---
StyleLoss:updateOutput input 1: 81.688522338867
StyleLoss:updateOutput output 1: 81.688522338867
StyleLoss:updateGradInput input 1: 81.688522338867
StyleLoss:updateOutput self.G 1: 6939956
StyleLoss:updateOutput self.G 2: 14.119379997253
StyleLoss:updateGradInput self.gradInput 1: -1.4955918459236e-07
StyleLoss:updateGradInput self.gradInput 2: -0.00089735502842814
dG 1: -5.1153062941012e-07
dG 2: -1.0407115707406e-12
---
Iteration 13 / 2500
Content 1 loss: 4861572.265625
Style 1 loss: 872.410744
Style 2 loss: 763955.474854
Style 3 loss: 2681525.207520
Style 4 loss: 666855.560303
Style 5 loss: 50125.997543
Total loss: 9024906.916589
optim value: -7.1667380332947
---
x1 value: -7.1667380332947
gram updateOutput value: 6.7258973121643
gram updateOutput value 2: 104682336
gram updateOutput value: 247.32830810547
gram updateOutput value 2: 1928902016
gram updateOutput value: 216.9172668457
gram updateOutput value 2: 846951488
gram updateOutput value: 47.782230377197
gram updateOutput value 2: 94079912
gram updateOutput value: 14.119379997253
gram updateOutput value 2: 6975083.5
gram 1 value: 3.5238169715512e-08
gram 2 value: 7.0476339431025e-08
gram 3 value: 7.0476339431025e-08
gram 1 value: 9.8604239440192e-08
gram 2 value: 1.9720847888038e-07
gram 3 value: 1.9720847888038e-07
gram 1 value: 6.094604145801e-07
gram 2 value: 1.2189208291602e-06
gram 3 value: 1.2189208291602e-06
gram 1 value: 4.0814336443873e-07
gram 2 value: 8.1628672887746e-07
gram 3 value: 8.1628672887746e-07
gram 1 value: -4.5060954967369e-09
gram 2 value: -9.0121909934737e-09
gram 3 value: -9.0121909934737e-09
feval(x) grad value: 0.001320191193372
---
StyleLoss:updateOutput input 1: 18.659908294678
StyleLoss:updateOutput output 1: 18.659908294678
StyleLoss:updateGradInput input 1: 18.659908294678
StyleLoss:updateOutput self.G 1: 104682336
StyleLoss:updateOutput self.G 2: 6.7255806922913
StyleLoss:updateGradInput self.gradInput 1: -3.6919203694197e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00061329017626122
dG 1: -4.2653195123421e-05
dG 2: -2.7403626243205e-12
---
StyleLoss:updateOutput input 1: 168.00694274902
StyleLoss:updateOutput output 1: 168.00694274902
StyleLoss:updateGradInput input 1: 168.00694274902
StyleLoss:updateOutput self.G 1: 1928902016
StyleLoss:updateOutput self.G 2: 247.3337097168
StyleLoss:updateGradInput self.gradInput 1: 3.4080898103639e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00015526062634308
dG 1: 8.3698389062192e-05
dG 2: 1.0732236280231e-11
---
StyleLoss:updateOutput input 1: 225.67362976074
StyleLoss:updateOutput output 1: 225.67362976074
StyleLoss:updateGradInput input 1: 225.67362976074
StyleLoss:updateOutput self.G 1: 846951488
StyleLoss:updateOutput self.G 2: 217.2008972168
StyleLoss:updateGradInput self.gradInput 1: 5.0181380828462e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00027899967972189
dG 1: 3.0907067412045e-05
dG 2: 7.9261250340856e-12
---
StyleLoss:updateOutput input 1: 147.89624023438
StyleLoss:updateOutput output 1: 147.89624023438
StyleLoss:updateGradInput input 1: 147.89624023438
StyleLoss:updateOutput self.G 1: 94079912
StyleLoss:updateOutput self.G 2: 47.851524353027
StyleLoss:updateGradInput self.gradInput 1: 5.7265602038115e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00025988553534262
dG 1: 1.3055080216873e-06
dG 2: 6.6401582583114e-13
---
StyleLoss:updateOutput input 1: 81.79012298584
StyleLoss:updateOutput output 1: 81.79012298584
StyleLoss:updateGradInput input 1: 81.79012298584
StyleLoss:updateOutput self.G 1: 6975083.5
StyleLoss:updateOutput self.G 2: 14.190845489502
StyleLoss:updateGradInput self.gradInput 1: 1.0725393906341e-07
StyleLoss:updateGradInput self.gradInput 2: 0.00064352358458564
dG 1: 3.3704996127426e-08
dG 2: 6.8573049799223e-14
---
Iteration 14 / 2500
Content 1 loss: 4879624.609375
Style 1 loss: 795.634747
Style 2 loss: 658082.885742
Style 3 loss: 2375763.244629
Style 4 loss: 619096.939087
Style 5 loss: 47465.947151
Total loss: 8580829.260731
optim value: -7.1730690002441
---
x1 value: -7.1730690002441
gram updateOutput value: 6.7255806922913
gram updateOutput value 2: 104547128
gram updateOutput value: 247.3337097168
gram updateOutput value 2: 1926148352
gram updateOutput value: 217.2008972168
gram updateOutput value 2: 845544576
gram updateOutput value: 47.851524353027
gram updateOutput value 2: 93681432
gram updateOutput value: 14.190845489502
gram updateOutput value 2: 6923787
gram 1 value: -6.6787713137728e-08
gram 2 value: -1.3357542627546e-07
gram 3 value: -1.3357542627546e-07
gram 1 value: 2.6953017595588e-09
gram 2 value: 5.3906035191176e-09
gram 3 value: 5.3906035191176e-09
gram 1 value: 3.5205343351663e-07
gram 2 value: 7.0410686703326e-07
gram 3 value: 7.0410686703326e-07
gram 1 value: 2.5267934233852e-07
gram 2 value: 5.0535868467705e-07
gram 3 value: 5.0535868467705e-07
gram 1 value: -4.8676875863407e-09
gram 2 value: -9.7353751726814e-09
gram 3 value: -9.7353751726814e-09
feval(x) grad value: 0.0038898827042431
---
StyleLoss:updateOutput input 1: 18.632427215576
StyleLoss:updateOutput output 1: 18.632427215576
StyleLoss:updateGradInput input 1: 18.632427215576
StyleLoss:updateOutput self.G 1: 104547128
StyleLoss:updateOutput self.G 2: 6.7168955802917
StyleLoss:updateGradInput self.gradInput 1: -4.0665359080094e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00023692530521657
dG 1: -4.6894234401407e-05
dG 2: -3.0128393269796e-12
---
StyleLoss:updateOutput input 1: 167.75993347168
StyleLoss:updateOutput output 1: 167.75993347168
StyleLoss:updateGradInput input 1: 167.75993347168
StyleLoss:updateOutput self.G 1: 1926148352
StyleLoss:updateOutput self.G 2: 246.98062133789
StyleLoss:updateGradInput self.gradInput 1: 2.3400197335377e-08
StyleLoss:updateGradInput self.gradInput 2: 5.0002858188236e-05
dG 1: 4.0594535676064e-05
dG 2: 5.2052381502299e-12
---
StyleLoss:updateOutput input 1: 225.32760620117
StyleLoss:updateOutput output 1: 225.32760620117
StyleLoss:updateGradInput input 1: 225.32760620117
StyleLoss:updateOutput self.G 1: 845544576
StyleLoss:updateOutput self.G 2: 216.84014892578
StyleLoss:updateGradInput self.gradInput 1: 3.2031511665309e-08
StyleLoss:updateGradInput self.gradInput 2: 0.00018118631851394
dG 1: 1.989624252019e-05
dG 2: 5.1023959363183e-12
---
StyleLoss:updateOutput input 1: 147.44709777832
StyleLoss:updateOutput output 1: 147.44709777832
StyleLoss:updateGradInput input 1: 147.44709777832
StyleLoss:updateOutput self.G 1: 93681432
StyleLoss:updateOutput self.G 2: 47.648838043213
StyleLoss:updateGradInput self.gradInput 1: 1.70006819733e-09
StyleLoss:updateGradInput self.gradInput 2: -5.8997444284614e-05
dG 1: -2.4083075800263e-07
dG 2: -1.2249289039687e-13
---
StyleLoss:updateOutput input 1: 81.416519165039
StyleLoss:updateOutput output 1: 81.416519165039
StyleLoss:updateGradInput input 1: 81.416519165039
StyleLoss:updateOutput self.G 1: 6923787
StyleLoss:updateOutput self.G 2: 14.08648109436
StyleLoss:updateGradInput self.gradInput 1: -2.1378372139225e-07
StyleLoss:updateGradInput self.gradInput 2: -0.0012827020836994
dG 1: -7.6250654501564e-07
dG 2: -1.5513236311868e-12
---
Iteration 15 / 2500
Content 1 loss: 4873029.296875
Style 1 loss: 763.334960
Style 2 loss: 561487.884521
Style 3 loss: 2117104.980469
Style 4 loss: 577939.361572
Style 5 loss: 45393.164635
Total loss: 8175718.023032
optim value: -7.1820588111877
---
x1 value: -7.1820588111877
gram updateOutput value: 6.7168955802917
gram updateOutput value 2: 104485936
gram updateOutput value: 246.98062133789
gram updateOutput value 2: 1924967808
gram updateOutput value: 216.84014892578
gram updateOutput value 2: 846940544
gram updateOutput value: 47.648838043213
gram updateOutput value 2: 94067216
gram updateOutput value: 14.08648109436
gram updateOutput value 2: 7041213.5
gram 1 value: 1.7093260851198e-07
gram 2 value: 3.4186521702395e-07
gram 3 value: 3.4186521702395e-07
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