(self, x)
| 132 | return nn.Sequential(*layers) |
| 133 | |
| 134 | def forward(self, x): |
| 135 | out = F.relu(self.bn1(self.conv1(x))) |
| 136 | out = self.layer1(out) |
| 137 | out = self.layer2(out) |
| 138 | out = self.layer3(out) |
| 139 | # out = F.avg_pool2d(out, 8) |
| 140 | # out = out.view(out.shape[0], -1) |
| 141 | out = self.avgpool(out) |
| 142 | out = torch.flatten(out, 1) |
| 143 | out = self.linear(out) |
| 144 | return out |
| 145 | |
| 146 | |
| 147 | def resnet18(in_dims, out_dims): |
nothing calls this directly
no outgoing calls
no test coverage detected