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import torch | |
from torch import nn | |
from torch.nn import Module | |
from models.config import VocoderModelConfig | |
from .discriminator_p import DiscriminatorP | |
class MultiPeriodDiscriminator(Module): | |
r"""MultiPeriodDiscriminator is a class that implements a multi-period discriminator network for the UnivNet vocoder. | |
Args: | |
model_config (VocoderModelConfig): The configuration object for the UnivNet vocoder model. | |
""" | |
def __init__( | |
self, | |
model_config: VocoderModelConfig, | |
): | |
super().__init__() | |
self.discriminators = nn.ModuleList( | |
[ | |
DiscriminatorP(period, model_config=model_config) | |
for period in model_config.mpd.periods | |
], | |
) | |
def forward(self, x: torch.Tensor) -> list[torch.Tensor]: | |
r"""Forward pass of the multi-period discriminator network. | |
Args: | |
x (torch.Tensor): The input tensor of shape (batch_size, channels, time_steps). | |
Returns: | |
list: A list of output tensors from each discriminator network. | |
""" | |
return [disc(x) for disc in self.discriminators] | |