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chenxuanhong
2022-02-17 16:30:33 +08:00
parent d82e46f0e7
commit 913e4916d4
17 changed files with 45302 additions and 71 deletions
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components/Generator_modulation_up.py
+6 -6
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@@ -5,7 +5,7 @@
# Created Date: Sunday January 16th 2022
# Author: Chen Xuanhong
# Email: chenxuanhongzju@outlook.com
# Last Modified: Sunday, 13th February 2022 1:35:21 pm
# Last Modified: Wednesday, 16th February 2022 1:34:58 am
# Modified By: Chen Xuanhong
# Copyright (c) 2022 Shanghai Jiao Tong University
#############################################################
@@ -107,7 +107,7 @@ class Generator(nn.Module):
):
super().__init__()
chn = kwargs["g_conv_dim"]
chn = kwargs["id_dim"]
k_size = kwargs["g_kernel_size"]
res_num = kwargs["res_num"]
@@ -121,16 +121,16 @@ class Generator(nn.Module):
self.first_layer = nn.Sequential(nn.Conv2d(3, 64, kernel_size=3, padding=1, bias=False),
nn.BatchNorm2d(64), activation)
### downsample
self.down1 = nn.Sequential(nn.Conv2d(64, 128, kernel_size=3, stride=2, padding=1),
self.down1 = nn.Sequential(nn.Conv2d(64, 128, kernel_size=3, stride=2, padding=1, bias=False),
nn.BatchNorm2d(128), activation)
self.down2 = nn.Sequential(nn.Conv2d(128, 256, kernel_size=3, stride=2, padding=1),
self.down2 = nn.Sequential(nn.Conv2d(128, 256, kernel_size=3, stride=2, padding=1, bias=False),
nn.BatchNorm2d(256), activation)
self.down3 = nn.Sequential(nn.Conv2d(256, 512, kernel_size=3, stride=2, padding=1),
self.down3 = nn.Sequential(nn.Conv2d(256, 512, kernel_size=3, stride=2, padding=1, bias=False),
nn.BatchNorm2d(512), activation)
self.down4 = nn.Sequential(nn.Conv2d(512, 512, kernel_size=3, stride=2, padding=1),
self.down4 = nn.Sequential(nn.Conv2d(512, 512, kernel_size=3, stride=2, padding=1, bias=False),
nn.BatchNorm2d(512), activation)
### resnet blocks