mirror of https://github.com/coqui-ai/TTS.git
40 lines
1.5 KiB
Python
40 lines
1.5 KiB
Python
import torch
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from mozilla_voice_tts.vocoder.models.melgan_generator import MelganGenerator
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from mozilla_voice_tts.vocoder.layers.pqmf import PQMF
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class MultibandMelganGenerator(MelganGenerator):
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def __init__(self,
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in_channels=80,
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out_channels=4,
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proj_kernel=7,
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base_channels=384,
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upsample_factors=(2, 8, 2, 2),
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res_kernel=3,
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num_res_blocks=3):
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super(MultibandMelganGenerator,
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self).__init__(in_channels=in_channels,
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out_channels=out_channels,
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proj_kernel=proj_kernel,
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base_channels=base_channels,
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upsample_factors=upsample_factors,
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res_kernel=res_kernel,
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num_res_blocks=num_res_blocks)
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self.pqmf_layer = PQMF(N=4, taps=62, cutoff=0.15, beta=9.0)
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def pqmf_analysis(self, x):
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return self.pqmf_layer.analysis(x)
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def pqmf_synthesis(self, x):
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return self.pqmf_layer.synthesis(x)
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@torch.no_grad()
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def inference(self, cond_features):
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cond_features = cond_features.to(self.layers[1].weight.device)
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cond_features = torch.nn.functional.pad(
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cond_features,
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(self.inference_padding, self.inference_padding),
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'replicate')
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return self.pqmf_synthesis(self.layers(cond_features))
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