(self, x)
| 220 | self.classifier=nn.Conv2d(128, num_classes, 1) |
| 221 | |
| 222 | def forward(self, x): |
| 223 | #intput_shape=x.shape[-2:] |
| 224 | x8, x16=x["8"],x["16"] |
| 225 | x16=self.head16(x16) |
| 226 | x16 = F.interpolate(x16, size=x8.shape[-2:], mode='bilinear', align_corners=False) |
| 227 | x8=self.head8(x8) |
| 228 | x=torch.cat((x8, x16), dim=1) |
| 229 | x=self.conv(x) |
| 230 | x=self.classifier(x) |
| 231 | return x |
| 232 | |
| 233 | class Exp2_Decoder12(nn.Module): |
| 234 | def __init__(self, num_classes, channels): |
nothing calls this directly
no outgoing calls
no test coverage detected