(self, x)
| 157 | self.fc2 = nn.Linear(128, 10) |
| 158 | |
| 159 | def forward(self, x): |
| 160 | x = self.conv1(x) |
| 161 | x = F.relu(x) |
| 162 | x = self.conv2(x) |
| 163 | x = F.relu(x) |
| 164 | x = F.max_pool2d(x, 2) |
| 165 | x = self.dropout1(x) |
| 166 | x = torch.flatten(x, 1) |
| 167 | x = self.fc1(x) |
| 168 | x = F.relu(x) |
| 169 | x = self.dropout2(x) |
| 170 | x = self.fc2(x) |
| 171 | output = F.log_softmax(x, dim=1) |
| 172 | return output |
| 173 | |
| 174 | # MNIST Test dataset and dataloader declaration |
| 175 | test_loader = torch.utils.data.DataLoader( |
nothing calls this directly
no outgoing calls
no test coverage detected