(self, net, inp, corr, flow, upsample=True)
| 138 | nn.Conv2d(256, 64*9, 1, padding=0)) |
| 139 | |
| 140 | def forward(self, net, inp, corr, flow, upsample=True): |
| 141 | motion_features = self.encoder(flow, corr) |
| 142 | inp = torch.cat([inp, motion_features], dim=1) |
| 143 | |
| 144 | net = self.gru(net, inp) |
| 145 | delta_flow = self.flow_head(net) |
| 146 | delta_flow = delta_flow[:, :2] |
| 147 | |
| 148 | # scale mask to balence gradients |
| 149 | mask = .25 * self.mask(net) |
| 150 | return net, mask, delta_flow |
| 151 | |
| 152 |
nothing calls this directly
no outgoing calls
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