mirror of
https://github.com/unanmed/ginka-generator.git
synced 2026-05-19 00:01:13 +08:00
42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
import torch
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import torch.nn as nn
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from ..common.common import ConvFusionModule
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from ..common.cond import ConditionInjector
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class StageHead(nn.Module):
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def __init__(self, in_ch, out_ch, out_size=(13, 13)):
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super().__init__()
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self.dec = ConvFusionModule(in_ch, in_ch*2, in_ch, 32, 32)
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self.pool = nn.Sequential(
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ConvFusionModule(in_ch, in_ch*2, in_ch*2, 32, 32),
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ConvFusionModule(in_ch*2, in_ch*2, in_ch, 32, 32),
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nn.AdaptiveMaxPool2d(out_size),
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nn.Conv2d(in_ch, out_ch, 1)
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)
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self.inject = ConditionInjector(256, in_ch)
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def forward(self, x, cond):
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x = self.dec(x)
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x = self.inject(x, cond)
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x = self.pool(x)
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return x
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class GinkaOutput(nn.Module):
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def __init__(self, in_ch=64, out_ch=32, out_size=(13, 13)):
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super().__init__()
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self.head1 = StageHead(in_ch, out_ch, out_size)
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self.head2 = StageHead(in_ch, out_ch, out_size)
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self.head3 = StageHead(in_ch, out_ch, out_size)
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def forward(self, x, stage, cond):
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if stage == 1:
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x = self.head1(x, cond)
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elif stage == 2:
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x = self.head2(x, cond)
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elif stage == 3:
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x = self.head3(x, cond)
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else:
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raise RuntimeError("Unknown generate stage.")
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return x
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