diff options
Diffstat (limited to 'become_yukarin/model')
| -rw-r--r-- | become_yukarin/model/model.py | 14 | ||||
| -rw-r--r-- | become_yukarin/model/sr_model.py | 10 |
2 files changed, 12 insertions, 12 deletions
diff --git a/become_yukarin/model/model.py b/become_yukarin/model/model.py index fc2d722..71fb805 100644 --- a/become_yukarin/model/model.py +++ b/become_yukarin/model/model.py @@ -70,7 +70,7 @@ class ConvHighway(chainer.link.Chain): class PreNet(chainer.link.Chain): - def __init__(self, in_channels: int, hidden_channels: int, out_channels: int): + def __init__(self, in_channels: int, hidden_channels: int, out_channels: int) -> None: super().__init__() with self.init_scope(): self.conv1 = Convolution1D(in_channels, hidden_channels, 1) @@ -84,7 +84,7 @@ class PreNet(chainer.link.Chain): class Conv1DBank(chainer.link.Chain): - def __init__(self, in_channels: int, out_channels: int, k: int): + def __init__(self, in_channels: int, out_channels: int, k: int) -> None: super().__init__() self.stacked_channels = out_channels * k self.pads = [ @@ -106,7 +106,7 @@ class Conv1DBank(chainer.link.Chain): class Conv1DProjections(chainer.link.Chain): - def __init__(self, in_channels: int, hidden_channels: int, out_channels: int): + def __init__(self, in_channels: int, hidden_channels: int, out_channels: int) -> None: super().__init__() with self.init_scope(): @@ -133,7 +133,7 @@ class CBHG(chainer.link.Chain): highway_layers: int, out_channels: int, disable_last_rnn: bool, - ): + ) -> None: super().__init__() self.max_pooling_padding = partial( chainer.functions.pad, @@ -182,7 +182,7 @@ class CBHG(chainer.link.Chain): class Predictor(chainer.link.Chain): - def __init__(self, network, out_size: int): + def __init__(self, network, out_size: int) -> None: super().__init__() with self.init_scope(): self.network = network @@ -196,7 +196,7 @@ class Predictor(chainer.link.Chain): class Aligner(chainer.link.Chain): - def __init__(self, in_size: int, out_time_length: int): + def __init__(self, in_size: int, out_time_length: int) -> None: super().__init__() with self.init_scope(): self.gru = chainer.links.NStepBiGRU( @@ -222,7 +222,7 @@ class Aligner(chainer.link.Chain): class Discriminator(chainer.link.Chain): - def __init__(self, in_channels: int, hidden_channels_list: List[int]): + def __init__(self, in_channels: int, hidden_channels_list: List[int]) -> None: super().__init__() with self.init_scope(): self.convs = chainer.link.ChainList(*( diff --git a/become_yukarin/model/sr_model.py b/become_yukarin/model/sr_model.py index 2e83526..f8e55d6 100644 --- a/become_yukarin/model/sr_model.py +++ b/become_yukarin/model/sr_model.py @@ -6,7 +6,7 @@ from become_yukarin.config.sr_config import SRModelConfig class CBR(chainer.Chain): - def __init__(self, ch0, ch1, bn=True, sample='down', activation=F.relu, dropout=False): + def __init__(self, ch0, ch1, bn=True, sample='down', activation=F.relu, dropout=False) -> None: super().__init__() self.bn = bn self.activation = activation @@ -33,7 +33,7 @@ class CBR(chainer.Chain): class Encoder(chainer.Chain): - def __init__(self, in_ch): + def __init__(self, in_ch) -> None: super().__init__() w = chainer.initializers.Normal(0.02) with self.init_scope(): @@ -54,7 +54,7 @@ class Encoder(chainer.Chain): class Decoder(chainer.Chain): - def __init__(self, out_ch): + def __init__(self, out_ch) -> None: super().__init__() w = chainer.initializers.Normal(0.02) with self.init_scope(): @@ -79,7 +79,7 @@ class Decoder(chainer.Chain): class SRPredictor(chainer.Chain): - def __init__(self, in_ch, out_ch): + def __init__(self, in_ch, out_ch) -> None: super().__init__() with self.init_scope(): self.encoder = Encoder(in_ch) @@ -90,7 +90,7 @@ class SRPredictor(chainer.Chain): class SRDiscriminator(chainer.Chain): - def __init__(self, in_ch, out_ch): + def __init__(self, in_ch, out_ch) -> None: super().__init__() w = chainer.initializers.Normal(0.02) with self.init_scope(): |