(self, norm_act=InPlaceABN)
| 690 | output 3 levels of features using a FPN structure |
| 691 | """ |
| 692 | def __init__(self, norm_act=InPlaceABN): |
| 693 | super(FeatureNet, self).__init__() |
| 694 | |
| 695 | self.conv0 = nn.Sequential( |
| 696 | ConvBnReLU(3, 8, 3, 1, 1, norm_act=norm_act), |
| 697 | ConvBnReLU(8, 8, 3, 1, 1, norm_act=norm_act)) |
| 698 | |
| 699 | self.conv1 = nn.Sequential( |
| 700 | ConvBnReLU(8, 16, 5, 2, 2, norm_act=norm_act), |
| 701 | ConvBnReLU(16, 16, 3, 1, 1, norm_act=norm_act), |
| 702 | ConvBnReLU(16, 16, 3, 1, 1, norm_act=norm_act)) |
| 703 | |
| 704 | self.conv2 = nn.Sequential( |
| 705 | ConvBnReLU(16, 32, 5, 2, 2, norm_act=norm_act), |
| 706 | ConvBnReLU(32, 32, 3, 1, 1, norm_act=norm_act), |
| 707 | ConvBnReLU(32, 32, 3, 1, 1, norm_act=norm_act)) |
| 708 | |
| 709 | self.toplayer = nn.Conv2d(32, 32, 1) |
| 710 | |
| 711 | def _upsample_add(self, x, y): |
| 712 | return F.interpolate(x, scale_factor=2, |
nothing calls this directly
no test coverage detected