(self, weight, features)
| 81 | # torch.nn.init.normal_(self.delta_proj[1].weight, std=1e-3) |
| 82 | |
| 83 | def forward(self, weight, features): |
| 84 | pos_emb = self.pos_emb_proj(self.block_pos_emb[:, :weight.size(1)].clone().detach()) |
| 85 | h = weight + pos_emb |
| 86 | for decoder in self.decoder_model: |
| 87 | h = decoder(h, context=features) |
| 88 | weight = weight + self.delta_proj(h) |
| 89 | return weight |
| 90 | |
| 91 | |
| 92 | class ImgWeightGenerator(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected