| 10 | |
| 11 | |
| 12 | def conv(use_batch_norm, in_planes, out_planes, kernel_size=3, stride=1): |
| 13 | if use_batch_norm: |
| 14 | return nn.Sequential( |
| 15 | nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, |
| 16 | stride=stride, padding=(kernel_size - 1) // 2, |
| 17 | bias=False), |
| 18 | nn.BatchNorm2d(out_planes), |
| 19 | nn.LeakyReLU(0.1, inplace=True) |
| 20 | ) |
| 21 | else: |
| 22 | return nn.Sequential( |
| 23 | nn.Conv2d( |
| 24 | in_planes, |
| 25 | out_planes, |
| 26 | kernel_size=kernel_size, |
| 27 | stride=stride, |
| 28 | padding=( |
| 29 | kernel_size - 1) // 2, |
| 30 | bias=True), |
| 31 | nn.LeakyReLU( |
| 32 | 0.1, |
| 33 | inplace=True)) |
| 34 | |
| 35 | |
| 36 | def i_conv(use_batch_norm, in_planes, out_planes, kernel_size=3, stride=1, |