(self, x)
| 459 | self.init_weights() |
| 460 | |
| 461 | def forward(self, x): |
| 462 | conv1 = self.conv1(x) |
| 463 | conv2 = self.conv2(conv1) |
| 464 | conv3 = self.conv3(conv2) |
| 465 | conv4 = self.conv4(conv3) |
| 466 | conv5 = self.conv5(conv4) |
| 467 | |
| 468 | outputs = conv5 |
| 469 | if self.use_sigmoid: |
| 470 | outputs = torch.sigmoid(conv5) |
| 471 | |
| 472 | return outputs, [conv1, conv2, conv3, conv4, conv5] |
| 473 | |
| 474 | class ResnetBlock(nn.Module): |
| 475 | def __init__(self, dim, dilation=1): |
nothing calls this directly
no outgoing calls
no test coverage detected