Spaces:
Sleeping
Sleeping
File size: 1,044 Bytes
37163a6 2279ae0 37163a6 2279ae0 37163a6 2279ae0 37163a6 2279ae0 37163a6 2279ae0 37163a6 2279ae0 37163a6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
import torch.nn as nn
from models import register
from .model import Encoder, Decoder, WNConv1d
default_configs = {
'snake': dict(
d_model=64,
strides=[2, 4, 5, 8],
d_latent=64,
d_in=1,
activation='snake',
),
'snakebeta': dict(
d_model=64,
strides=[2, 4, 5, 8],
d_latent=64,
d_in=1,
activation='snakebeta',
),
}
@register('dac_encoder')
def make_dac_encoder(config_name, **kwargs):
encoder_kwargs = default_configs[config_name]
encoder_kwargs.update(kwargs)
d_model = encoder_kwargs['d_model']
return nn.Sequential(
Encoder(**encoder_kwargs),
WNConv1d(d_model, d_model, kernel_size=1),
)
@register('vqgan_decoder')
def make_vqgan_decoder(config_name, **kwargs):
decoder_kwargs = default_configs[config_name]
decoder_kwargs.update(kwargs)
d_model = decoder_kwargs['d_model']
return nn.Sequential(
WNConv1d(d_model, d_model, kernel_size=1),
Decoder(**decoder_kwargs),
)
|