(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dilation=1)
| 11 | ) |
| 12 | |
| 13 | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dilation=1): |
| 14 | return nn.Sequential( |
| 15 | nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, |
| 16 | padding=padding, dilation=dilation, bias=True), |
| 17 | nn.PReLU(out_planes) |
| 18 | ) |
| 19 | |
| 20 | class IFBlock(nn.Module): |
| 21 | def __init__(self, in_planes, c=64): |