(self, flow, corr)
| 97 | self.conv = nn.Conv2d(64+192, 128-2, 3, padding=1) |
| 98 | |
| 99 | def forward(self, flow, corr): |
| 100 | cor = F.relu(self.convc1(corr)) |
| 101 | cor = F.relu(self.convc2(cor)) |
| 102 | flo = F.relu(self.convf1(flow)) |
| 103 | flo = F.relu(self.convf2(flo)) |
| 104 | |
| 105 | cor_flo = torch.cat([cor, flo], dim=1) |
| 106 | out = F.relu(self.conv(cor_flo)) |
| 107 | return torch.cat([out, flow], dim=1) |
| 108 | |
| 109 | class SmallUpdateBlock(nn.Module): |
| 110 | def __init__(self, args, hidden_dim=96): |
nothing calls this directly
no outgoing calls
no test coverage detected