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import torch
from TTS.vocoder.layers.pqmf import PQMF
from TTS.vocoder.models.melgan_generator import MelganGenerator
class MultibandMelganGenerator(MelganGenerator):
def __init__(
self,
in_channels=80,
out_channels=4,
proj_kernel=7,
base_channels=384,
upsample_factors=(2, 8, 2, 2),
res_kernel=3,
num_res_blocks=3,
):
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,
)
self.pqmf_layer = PQMF(N=4, taps=62, cutoff=0.15, beta=9.0)
def pqmf_analysis(self, x):
return self.pqmf_layer.analysis(x)
def pqmf_synthesis(self, x):
return self.pqmf_layer.synthesis(x)
@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.pqmf_synthesis(self.layers(cond_features))
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