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@ProGamerGov
Created October 24, 2017 06:24
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-image_size 2432, -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 input value: 13.913771629333
gram updateOutput value: 0
gram updateOutput value 2: 1164591616
gram updateOutput input value: 96.735000610352
gram updateOutput value: 0
gram updateOutput value 2: 14068302848
gram updateOutput input value: 106.94290924072
gram updateOutput value: 0
gram updateOutput value 2: 4332710400
gram updateOutput input value: 54.167041778564
gram updateOutput value: 0
gram updateOutput value 2: 274163968
gram updateOutput input value: 10.34401512146
gram updateOutput value: 0
gram updateOutput value 2: 3434939.25
Capturing style target 1
gram updateOutput input value: 14.171918869019
gram updateOutput value: 3.3136463165283
gram updateOutput value 2: 231200432
gram updateOutput input value: 115.11059570312
gram updateOutput value: 80.057891845703
gram updateOutput value 2: 3753993984
gram updateOutput input value: 163.39628601074
gram updateOutput value: 49.26831817627
gram updateOutput value 2: 1826164992
gram updateOutput input value: 103.54053497314
gram updateOutput value: 6.2241559028625
gram updateOutput value 2: 176804336
gram updateOutput input value: 45.066600799561
gram updateOutput value: 0.31082594394684
gram updateOutput value 2: 8545173
3.8834133148193
125.94509124756
122.21520233154
23.665088653564
4.5750517845154
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.8834133148193
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 125.94509124756
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 122.21520233154
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 23.665088653564
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 4.5750517845154
gram updateOutput value 2: 40656444
y value: 41.496166229248
dy value: 0
Running optimization with ADAM
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 118.95206451416
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
gram updateOutput value 2: 40656444
x2 value: -7.1936044692993
gram 1 value: -1.6226302079758e-08
gram 2 value: -3.2452604159516e-08
gram 3 value: -3.2452604159516e-08
gram 1 value: -2.9464816364566e-08
gram 2 value: -5.8929632729132e-08
gram 3 value: -5.8929632729132e-08
gram 1 value: -2.6448416790004e-08
gram 2 value: -5.2896833580007e-08
gram 3 value: -5.2896833580007e-08
gram 1 value: -1.174338990495e-07
gram 2 value: -2.34867798099e-07
gram 3 value: -2.34867798099e-07
gram 1 value: -3.1889019203035e-10
gram 2 value: -6.377803840607e-10
gram 3 value: -6.377803840607e-10
feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
StyleLoss:updateOutput self.G 1: 1278823680
StyleLoss:updateOutput self.G 2: 3.6386742591858
StyleLoss:updateGradInput self.gradInput 1: -2.1727835086693e-09
StyleLoss:updateGradInput self.gradInput 2: -1.3036697964708e-05
dG 1: -0.00011950141924899
dG 2: -3.400208445966e-13
---
StyleLoss:updateOutput input 1: 112.44744110107
StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
StyleLoss:updateOutput self.G 1: 20267821056
StyleLoss:updateOutput self.G 2: 115.33726501465
StyleLoss:updateGradInput self.gradInput 1: -4.7330814822999e-09
StyleLoss:updateGradInput self.gradInput 2: -4.0275230276166e-05
dG 1: -0.001294901361689
dG 2: -7.3688399132577e-12
---
StyleLoss:updateOutput input 1: 163.86224365234
StyleLoss:updateOutput output 1: 163.86224365234
StyleLoss:updateGradInput input 1: 163.86224365234
StyleLoss:updateOutput self.G 1: 10460779520
StyleLoss:updateOutput self.G 2: 118.95206451416
StyleLoss:updateGradInput self.gradInput 1: -8.5812879024871e-10
StyleLoss:updateGradInput self.gradInput 2: -2.9808131785103e-06
dG 1: -9.958243026631e-05
dG 2: -1.1323762023549e-12
---
StyleLoss:updateOutput input 1: 98.696151733398
StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
StyleLoss:updateOutput self.G 2: 20.841968536377
StyleLoss:updateGradInput self.gradInput 1: -1.1896679197321e-08
StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
dG 1: -2.1538742657867e-05
dG 2: -4.8897913712889e-13
---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
StyleLoss:updateOutput self.G 2: 3.6789810657501
StyleLoss:updateGradInput self.gradInput 1: -7.1434293147377e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 1 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 118.95206451416
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
gram updateOutput value 2: 40656444
x2 value: -7.1936044692993
gram 1 value: -1.6226302079758e-08
gram 2 value: -3.2452604159516e-08
gram 3 value: -3.2452604159516e-08
gram 1 value: -2.9464816364566e-08
gram 2 value: -5.8929632729132e-08
gram 3 value: -5.8929632729132e-08
gram 1 value: -2.6448416790004e-08
gram 2 value: -5.2896833580007e-08
gram 3 value: -5.2896833580007e-08
gram 1 value: -1.174338990495e-07
gram 2 value: -2.34867798099e-07
gram 3 value: -2.34867798099e-07
gram 1 value: -3.1889019203035e-10
gram 2 value: -6.377803840607e-10
gram 3 value: -6.377803840607e-10
feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
StyleLoss:updateOutput self.G 1: 1278823680
StyleLoss:updateOutput self.G 2: 3.6386742591858
StyleLoss:updateGradInput self.gradInput 1: -2.1727835086693e-09
StyleLoss:updateGradInput self.gradInput 2: -1.3036697964708e-05
dG 1: -0.00011950141924899
dG 2: -3.400208445966e-13
---
StyleLoss:updateOutput input 1: 112.44744110107
StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
StyleLoss:updateOutput self.G 1: 20267821056
StyleLoss:updateOutput self.G 2: 115.33726501465
StyleLoss:updateGradInput self.gradInput 1: -4.7330814822999e-09
StyleLoss:updateGradInput self.gradInput 2: -4.0275226638187e-05
dG 1: -0.001294901361689
dG 2: -7.3688399132577e-12
---
StyleLoss:updateOutput input 1: 163.86224365234
StyleLoss:updateOutput output 1: 163.86224365234
StyleLoss:updateGradInput input 1: 163.86224365234
StyleLoss:updateOutput self.G 1: 10460779520
StyleLoss:updateOutput self.G 2: 118.95206451416
StyleLoss:updateGradInput self.gradInput 1: -8.5812879024871e-10
StyleLoss:updateGradInput self.gradInput 2: -2.9808131785103e-06
dG 1: -9.958243026631e-05
dG 2: -1.1323762023549e-12
---
StyleLoss:updateOutput input 1: 98.696151733398
StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
StyleLoss:updateOutput self.G 2: 20.841968536377
StyleLoss:updateGradInput self.gradInput 1: -1.1896679197321e-08
StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
dG 1: -2.1538742657867e-05
dG 2: -4.8897913712889e-13
---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
StyleLoss:updateOutput self.G 2: 3.6789810657501
StyleLoss:updateGradInput self.gradInput 1: -7.1434293147377e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 2 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 118.95206451416
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
gram updateOutput value 2: 40656444
x2 value: -7.1936044692993
gram 1 value: -1.6226302079758e-08
gram 2 value: -3.2452604159516e-08
gram 3 value: -3.2452604159516e-08
gram 1 value: -2.9464816364566e-08
gram 2 value: -5.8929632729132e-08
gram 3 value: -5.8929632729132e-08
gram 1 value: -2.6448416790004e-08
gram 2 value: -5.2896833580007e-08
gram 3 value: -5.2896833580007e-08
gram 1 value: -1.174338990495e-07
gram 2 value: -2.34867798099e-07
gram 3 value: -2.34867798099e-07
gram 1 value: -3.1889019203035e-10
gram 2 value: -6.377803840607e-10
gram 3 value: -6.377803840607e-10
feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
StyleLoss:updateOutput self.G 1: 1278823680
StyleLoss:updateOutput self.G 2: 3.6386742591858
StyleLoss:updateGradInput self.gradInput 1: -2.1727835086693e-09
StyleLoss:updateGradInput self.gradInput 2: -1.3036697964708e-05
dG 1: -0.00011950141924899
dG 2: -3.400208445966e-13
---
StyleLoss:updateOutput input 1: 112.44744110107
StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
StyleLoss:updateOutput self.G 1: 20267821056
StyleLoss:updateOutput self.G 2: 115.33726501465
StyleLoss:updateGradInput self.gradInput 1: -4.7330814822999e-09
StyleLoss:updateGradInput self.gradInput 2: -4.0275219362229e-05
dG 1: -0.001294901361689
dG 2: -7.3688399132577e-12
---
StyleLoss:updateOutput input 1: 163.86224365234
StyleLoss:updateOutput output 1: 163.86224365234
StyleLoss:updateGradInput input 1: 163.86224365234
StyleLoss:updateOutput self.G 1: 10460779520
StyleLoss:updateOutput self.G 2: 118.95206451416
StyleLoss:updateGradInput self.gradInput 1: -8.5812879024871e-10
StyleLoss:updateGradInput self.gradInput 2: -2.9808131785103e-06
dG 1: -9.958243026631e-05
dG 2: -1.1323762023549e-12
---
StyleLoss:updateOutput input 1: 98.696151733398
StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
StyleLoss:updateOutput self.G 2: 20.841968536377
StyleLoss:updateGradInput self.gradInput 1: -1.1896679197321e-08
StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
dG 1: -2.1538742657867e-05
dG 2: -4.8897913712889e-13
---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
StyleLoss:updateOutput self.G 2: 3.6789810657501
StyleLoss:updateGradInput self.gradInput 1: -7.1434293147377e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 3 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 118.95206451416
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
gram updateOutput value 2: 40656444
x2 value: -7.1936044692993
gram 1 value: -1.6226302079758e-08
gram 2 value: -3.2452604159516e-08
gram 3 value: -3.2452604159516e-08
gram 1 value: -2.9464816364566e-08
gram 2 value: -5.8929632729132e-08
gram 3 value: -5.8929632729132e-08
gram 1 value: -2.6448416790004e-08
gram 2 value: -5.2896833580007e-08
gram 3 value: -5.2896833580007e-08
gram 1 value: -1.174338990495e-07
gram 2 value: -2.34867798099e-07
gram 3 value: -2.34867798099e-07
gram 1 value: -3.1889019203035e-10
gram 2 value: -6.377803840607e-10
gram 3 value: -6.377803840607e-10
feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
StyleLoss:updateOutput self.G 1: 1278823680
StyleLoss:updateOutput self.G 2: 3.6386742591858
StyleLoss:updateGradInput self.gradInput 1: -2.1727835086693e-09
StyleLoss:updateGradInput self.gradInput 2: -1.3036697964708e-05
dG 1: -0.00011950141924899
dG 2: -3.400208445966e-13
---
StyleLoss:updateOutput input 1: 112.44744110107
StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
StyleLoss:updateOutput self.G 1: 20267821056
StyleLoss:updateOutput self.G 2: 115.33726501465
StyleLoss:updateGradInput self.gradInput 1: -4.7330814822999e-09
StyleLoss:updateGradInput self.gradInput 2: -4.0275226638187e-05
dG 1: -0.001294901361689
dG 2: -7.3688399132577e-12
---
StyleLoss:updateOutput input 1: 163.86224365234
StyleLoss:updateOutput output 1: 163.86224365234
StyleLoss:updateGradInput input 1: 163.86224365234
StyleLoss:updateOutput self.G 1: 10460779520
StyleLoss:updateOutput self.G 2: 118.95206451416
StyleLoss:updateGradInput self.gradInput 1: -8.5812879024871e-10
StyleLoss:updateGradInput self.gradInput 2: -2.9808124963893e-06
dG 1: -9.958243026631e-05
dG 2: -1.1323762023549e-12
---
StyleLoss:updateOutput input 1: 98.696151733398
StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
StyleLoss:updateOutput self.G 2: 20.841968536377
StyleLoss:updateGradInput self.gradInput 1: -1.1896679197321e-08
StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
dG 1: -2.1538742657867e-05
dG 2: -4.8897913712889e-13
---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
StyleLoss:updateOutput self.G 2: 3.6789810657501
StyleLoss:updateGradInput self.gradInput 1: -7.1434293147377e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 4 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
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feval(x) grad value: 0
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StyleLoss:updateGradInput input 1: 13.897933006287
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StyleLoss:updateOutput output 1: 41.496166229248
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dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 5 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
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gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
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gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
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gram updateOutput value 2: 10460779520
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gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
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gram 1 value: -3.1889019203035e-10
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feval(x) grad value: 0
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StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
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StyleLoss:updateOutput output 1: 112.44744110107
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StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
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StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
dG 1: -2.1538742657867e-05
dG 2: -4.8897913712889e-13
---
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StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
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StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 6 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
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gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
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gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
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gram updateOutput value 2: 10460779520
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gram updateOutput value: 20.841968536377
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gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
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gram 1 value: -3.1889019203035e-10
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feval(x) grad value: 0
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StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
StyleLoss:updateOutput self.G 1: 1278823680
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StyleLoss:updateOutput output 1: 112.44744110107
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StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
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StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
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---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
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StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 7 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
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gram updateOutput value 2: 10460779520
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gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
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gram 1 value: -3.1889019203035e-10
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feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
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StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
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---
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StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
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StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
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---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
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StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 8 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
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gram updateOutput value 2: 10460779520
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gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
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gram 1 value: -3.1889019203035e-10
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feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
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StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
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StyleLoss:updateOutput output 1: 163.86224365234
StyleLoss:updateGradInput input 1: 163.86224365234
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---
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StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
StyleLoss:updateOutput self.G 2: 20.841968536377
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StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
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---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
StyleLoss:updateOutput self.G 2: 3.6789810657501
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StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 9 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 118.95206451416
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
gram updateOutput value 2: 40656444
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gram 1 value: -3.1889019203035e-10
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gram 3 value: -6.377803840607e-10
feval(x) grad value: 0
---
StyleLoss:updateOutput input 1: 13.897933006287
StyleLoss:updateOutput output 1: 13.897933006287
StyleLoss:updateGradInput input 1: 13.897933006287
StyleLoss:updateOutput self.G 1: 1278823680
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StyleLoss:updateOutput output 1: 112.44744110107
StyleLoss:updateGradInput input 1: 112.44744110107
StyleLoss:updateOutput self.G 1: 20267821056
StyleLoss:updateOutput self.G 2: 115.33726501465
StyleLoss:updateGradInput self.gradInput 1: -4.7330814822999e-09
StyleLoss:updateGradInput self.gradInput 2: -4.0275226638187e-05
dG 1: -0.001294901361689
dG 2: -7.3688399132577e-12
---
StyleLoss:updateOutput input 1: 163.86224365234
StyleLoss:updateOutput output 1: 163.86224365234
StyleLoss:updateGradInput input 1: 163.86224365234
StyleLoss:updateOutput self.G 1: 10460779520
StyleLoss:updateOutput self.G 2: 118.95206451416
StyleLoss:updateGradInput self.gradInput 1: -8.5812879024871e-10
StyleLoss:updateGradInput self.gradInput 2: -2.9808131785103e-06
dG 1: -9.958243026631e-05
dG 2: -1.1323762023549e-12
---
StyleLoss:updateOutput input 1: 98.696151733398
StyleLoss:updateOutput output 1: 98.696151733398
StyleLoss:updateGradInput input 1: 98.696151733398
StyleLoss:updateOutput self.G 1: 918054848
StyleLoss:updateOutput self.G 2: 20.841968536377
StyleLoss:updateGradInput self.gradInput 1: -1.1896679197321e-08
StyleLoss:updateGradInput self.gradInput 2: -7.4847244832199e-05
dG 1: -2.1538742657867e-05
dG 2: -4.8897913712889e-13
---
StyleLoss:updateOutput input 1: 41.496166229248
StyleLoss:updateOutput output 1: 41.496166229248
StyleLoss:updateGradInput input 1: 41.496166229248
StyleLoss:updateOutput self.G 1: 40656444
StyleLoss:updateOutput self.G 2: 3.6789810657501
StyleLoss:updateGradInput self.gradInput 1: -7.1434293147377e-08
StyleLoss:updateGradInput self.gradInput 2: -0.00042860573739745
dG 1: -6.8364793150977e-06
dG 2: -6.1862955079775e-13
---
Iteration 10 / 2500
Content 1 loss: 1994813.281250
Style 1 loss: 2699.189365
Style 2 loss: 2853272.277832
Style 3 loss: 10104018.310547
Style 4 loss: 662611.404419
Style 5 loss: 25619.004250
Total loss: 15643033.467662
optim value: -7.1936044692993
---
x1 value: -7.1936044692993
gram updateOutput input value: 13.897933006287
gram updateOutput value: 3.6386742591858
gram updateOutput value 2: 1278823680
gram updateOutput input value: 112.44744110107
gram updateOutput value: 115.33726501465
gram updateOutput value 2: 20267821056
gram updateOutput input value: 163.86224365234
gram updateOutput value: 118.95206451416
gram updateOutput value 2: 10460779520
gram updateOutput input value: 98.696151733398
gram updateOutput value: 20.841968536377
gram updateOutput value 2: 918054848
gram updateOutput input value: 41.496166229248
gram updateOutput value: 3.6789810657501
gram updateOutput value 2: 40656444
x2 value: -7.1936044692993
gram 1 value: -1.6226302079758e-08
gram 2 value: -3.2452604159516e-08
gram 3 value: -3.2452604159516e-08
gram 1 value: -2.9464816364566e-08
gram 2 value: -5.8929632729132e-08
gram 3 value: -5.8929632729132e-08
gram 1 value: -2.6448416790004e-08
gram 2 value: -5.2896833580007e-08
gram 3 value: -5.2896833580007e-08
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