| 125 | |
| 126 | |
| 127 | class Aux_Module(nn.Module): |
| 128 | def __init__(self, in_planes, num_classes=19, sync_bn=False): |
| 129 | super(Aux_Module, self).__init__() |
| 130 | |
| 131 | norm_layer = get_syncbn() if sync_bn else nn.BatchNorm2d |
| 132 | self.aux = nn.Sequential( |
| 133 | nn.Conv2d(in_planes, 256, kernel_size=3, stride=1, padding=1), |
| 134 | norm_layer(256), |
| 135 | nn.ReLU(inplace=True), |
| 136 | nn.Dropout2d(0.1), |
| 137 | nn.Conv2d(256, num_classes, kernel_size=1, stride=1, padding=0, bias=True), |
| 138 | ) |
| 139 | |
| 140 | def forward(self, x): |
| 141 | res = self.aux(x) |
| 142 | return res |