(in_planes, out_planes, kernel_size=4, stride=2, padding=1)
| 22 | |
| 23 | |
| 24 | def deconv(in_planes, out_planes, kernel_size=4, stride=2, padding=1): |
| 25 | return nn.Sequential( |
| 26 | torch.nn.ConvTranspose2d(in_channels=in_planes, out_channels=out_planes, |
| 27 | kernel_size=4, stride=2, padding=1, bias=True), |
| 28 | nn.PReLU(out_planes) |
| 29 | ) |
| 30 | |
| 31 | def conv_woact(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dilation=1): |
| 32 | return nn.Sequential( |