def __init__(self,
rnn_dims,
fc_dims,
global_decoder_cond_dims,
upsample_factors,
normalize_vq=False,
noise_x=False,
noise_y=False):
super().__init__()
self.n_classes = 256
self.overtone = Overtone(rnn_dims, fc_dims, 128,
global_decoder_cond_dims)
self.vq = VectorQuant(1, 512, 128, normalize=normalize_vq)
self.noise_x = noise_x
self.noise_y = noise_y
encoder_layers = [
(2, 4, 1),
(2, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
]
self.encoder = DownsamplingEncoder(128, encoder_layers)
self.frame_advantage = 15
self.num_params()
def __init__(self, rnn_dims, fc_dims, global_decoder_cond_dims, upsample_factors, normalize_vq=False,
noise_x=False, noise_y=False):
super().__init__()
self.n_vq_classes = 512
self.n_f0_classes = 128
self.vec_len = 128
# self.channel_f0 = 128
#self.upsample = UpsampleNetwork_F0(upsample_factors)
#n_channels, n_classes, vec_len, normalize=False
self.vq = VectorQuant(1, self.n_vq_classes, self.vec_len, normalize=normalize_vq)
self.vq_f0 = VectorQuant(1, self.n_f0_classes, self.vec_len, normalize=normalize_vq)
#self.vq_f0 = VectorQuant(1, self.n_classes_f0, self.vec_len, normalize=normalize_vq)
self.noise_x = noise_x
self.noise_y = noise_y
encoder_layers_wave = [
(2, 4, 1),
(2, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
]
self.encoder = DownsamplingEncoder(128, encoder_layers_wave)
encoder_layers_f0 = [
(2, 4, 1),
(2, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
(2, 4, 1),
(1, 4, 1),
]
self.encoder_f0 = DownsamplingEncoder(128, encoder_layers_f0)
self.frame_advantage = 15
self.num_params()
self.overtone = Overtone_f0(rnn_dims, fc_dims,self.vec_len*2, global_decoder_cond_dims)