| 21 | |
| 22 | |
| 23 | class AlexNet(nn.Module): |
| 24 | def __init__(self): |
| 25 | super().__init__() |
| 26 | self.layers = models.alexnet(weights=models.AlexNet_Weights.IMAGENET1K_V1).features |
| 27 | self.channels = [] |
| 28 | for layer in self.layers: |
| 29 | if isinstance(layer, nn.Conv2d): |
| 30 | self.channels.append(layer.out_channels) |
| 31 | |
| 32 | def forward(self, x): |
| 33 | fmaps = [] |
| 34 | for layer in self.layers: |
| 35 | x = layer(x) |
| 36 | if isinstance(layer, nn.ReLU): |
| 37 | fmaps.append(x) |
| 38 | return fmaps |
| 39 | |
| 40 | |
| 41 | class Conv1x1(nn.Module): |