- Add new pretrained model to ./models/upconv_7 - Move old models to ./models/vgg_7 - Use nn.LeakyReLU instead of w2nn.LeakyReLU - Add useful attribute to .json New JSON attribute: The first layer has `model_config` attribute. It contains: model_arch: architecture name of model. see `lib/srcnn.lua` scale_factor: if scale_factor > 1, model:forward() changes image resolution with scale_factor. channels: input/output channels. if channels == 3, model is RGB model. offset: pixel size that is to be removed from output. for example: (scale_factor=1, offset=7, input=100x100) => output=(100-7)x(100-7) (scale_factor=2, offset=12, input=100x100) => output=(100*2-12)x(100*2-12) And each layer has `class_name` attribute.
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2
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5
|
|
train
|
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5
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|
0
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2
|
|
10
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|
gradWeight
|
|
4
|
|
27
|
|
3
|
|
V 1
|
|
16
|
|
torch.CudaTensor
|
|
2
|
|
32 288
|
|
288 1
|
|
1
|
|
4
|
|
28
|
|
3
|
|
V 1
|
|
17
|
|
torch.CudaStorage
|
|
9216
|
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5
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train
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5
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|
0
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2
|
|
10
|
|
gradWeight
|
|
4
|
|
43
|
|
3
|
|
V 1
|
|
16
|
|
torch.CudaTensor
|
|
2
|
|
64 288
|
|
288 1
|
|
1
|
|
4
|
|
44
|
|
3
|
|
V 1
|
|
17
|
|
torch.CudaStorage
|
|
18432
|
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torch.CudaTensor
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1
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128
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94
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1
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1
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4
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96
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3
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V 1
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17
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128
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padH
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0
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12
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4
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97
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3
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V 1
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|
12
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nn.LeakyReLU
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3
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98
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6
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2
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7
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inplace
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5
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1
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2
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5
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16
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2
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negval
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1
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0.10000000000000001
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99
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16
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0
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output
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100
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3
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V 1
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16
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101
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V 1
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23
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102
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dH
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dW
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nInputPlane
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128
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output
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103
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16
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kH
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gradInput
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104
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V 1
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16
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padW
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weight
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105
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V 1
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16
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torch.CudaTensor
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3 1152
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106
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V 1
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17
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torch.CudaStorage
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