summaryrefslogtreecommitdiff
path: root/become_yukarin/model/model.py
diff options
context:
space:
mode:
Diffstat (limited to 'become_yukarin/model/model.py')
-rw-r--r--become_yukarin/model/model.py14
1 files changed, 7 insertions, 7 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(*(