coqui-tts/vocoder/tf/models/multiband_melgan_generator.py

48 lines
1.7 KiB
Python

import tensorflow as tf
from TTS.vocoder.tf.models.melgan_generator import MelganGenerator
from TTS.vocoder.tf.layers.pqmf import PQMF
class MultibandMelganGenerator(MelganGenerator): # pylint: disable=too-many-ancestors
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(MultibandMelganGenerator,
self).__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)
# def call(self, c, training=False):
# if training:
# raise NotImplementedError()
# return self.inference(c)
def inference(self, c):
c = tf.transpose(c, perm=[0, 2, 1])
c = tf.expand_dims(c, 2)
# FIXME: TF had no replicate padding as in Torch
# c = tf.pad(c, [[0, 0], [self.inference_padding, self.inference_padding], [0, 0], [0, 0]], "REFLECT")
o = c
for layer in self.model_layers:
o = layer(o)
o = tf.transpose(o, perm=[0, 3, 2, 1])
o = self.pqmf_layer.synthesis(o[:, :, 0, :])
return o