| 13 | # phi_5,4 5th conv layer before maxpooling but after activation |
| 14 | |
| 15 | class VGGLoss(nn.Module): |
| 16 | def __init__(self): |
| 17 | super().__init__() |
| 18 | #features map = [1, 512, 14, 14] |
| 19 | self.vgg = vgg19(pretrained=True).features[:36].eval().to(config.DEVICE) |
| 20 | print(self.vgg) |
| 21 | self.loss = nn.MSELoss() |
| 22 | |
| 23 | for param in self.vgg.parameters(): |
| 24 | param.requires_grad = False |
| 25 | |
| 26 | def forward(self, input, target): |
| 27 | vgg_input_features = self.vgg(input) |
| 28 | vgg_target_features = self.vgg(target) |
| 29 | return self.loss(vgg_input_features, vgg_target_features) |
| 30 | |
| 31 | if __name__ == '__main__': |
| 32 | # vgg = vgg19(pretrained = True) |