(self)
| 156 | return self.log_dict |
| 157 | |
| 158 | def configure_optimizers(self): |
| 159 | lr = self.learning_rate |
| 160 | ae_params_list = list(self.encoder.parameters()) + list(self.decoder.parameters()) + list( |
| 161 | self.quant_conv.parameters()) + list(self.post_quant_conv.parameters()) |
| 162 | if self.learn_logvar: |
| 163 | print(f"{self.__class__.__name__}: Learning logvar") |
| 164 | ae_params_list.append(self.loss.logvar) |
| 165 | opt_ae = torch.optim.Adam(ae_params_list, |
| 166 | lr=lr, betas=(0.5, 0.9)) |
| 167 | opt_disc = torch.optim.Adam(self.loss.discriminator.parameters(), |
| 168 | lr=lr, betas=(0.5, 0.9)) |
| 169 | return [opt_ae, opt_disc], [] |
| 170 | |
| 171 | def get_last_layer(self): |
| 172 | return self.decoder.conv_out.weight |
nothing calls this directly
no outgoing calls
no test coverage detected