- 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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48
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V 1
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2
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5
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train
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0
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2
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10
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gradWeight
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75
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3
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V 1
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16
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torch.CudaTensor
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2
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128 576
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576 1
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1
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4
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76
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3
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V 1
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17
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torch.CudaStorage
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73728
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gradBias
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torch.CudaStorage
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nn.LeakyReLU
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