(self, features, num_classes=1000, init_weights=False)
| 15 | |
| 16 | class VGG(nn.Module): |
| 17 | def __init__(self, features, num_classes=1000, init_weights=False): |
| 18 | super(VGG, self).__init__() |
| 19 | self.features = features |
| 20 | self.classifier = nn.Sequential( |
| 21 | nn.Linear(512*7*7, 4096), |
| 22 | nn.ReLU(True), |
| 23 | nn.Dropout(p=0.5), |
| 24 | nn.Linear(4096, 4096), |
| 25 | nn.ReLU(True), |
| 26 | nn.Dropout(p=0.5), |
| 27 | nn.Linear(4096, num_classes) |
| 28 | ) |
| 29 | if init_weights: |
| 30 | self._initialize_weights() |
| 31 | |
| 32 | def forward(self, x): |
| 33 | # N x 3 x 224 x 224 |
nothing calls this directly
no test coverage detected