| import torch |
|
|
| from TTS.vocoder.models.melgan_generator import MelganGenerator |
|
|
|
|
| class FullbandMelganGenerator(MelganGenerator): |
| def __init__( |
| self, |
| in_channels=80, |
| out_channels=1, |
| proj_kernel=7, |
| base_channels=512, |
| upsample_factors=(2, 8, 2, 2), |
| res_kernel=3, |
| num_res_blocks=4, |
| ): |
| super().__init__( |
| in_channels=in_channels, |
| out_channels=out_channels, |
| proj_kernel=proj_kernel, |
| base_channels=base_channels, |
| upsample_factors=upsample_factors, |
| res_kernel=res_kernel, |
| num_res_blocks=num_res_blocks, |
| ) |
|
|
| @torch.no_grad() |
| def inference(self, cond_features): |
| cond_features = cond_features.to(self.layers[1].weight.device) |
| cond_features = torch.nn.functional.pad( |
| cond_features, (self.inference_padding, self.inference_padding), "replicate" |
| ) |
| return self.layers(cond_features) |
|
|
