- self.conv2 = nn.Conv2d( 32, 256, kernel_size=5, padding=2)
- self.conv3 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
- self.conv4 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
- self.conv5 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
- self.fc1 = nn.Linear(4096, 512)
+ self.conv2 = nn.Conv2d( 32, self.nb_channels, kernel_size=5, padding=2)
+ self.conv3 = nn.Conv2d(self.nb_channels, self.nb_channels, kernel_size=3, padding=1)
+ self.conv4 = nn.Conv2d(self.nb_channels, self.nb_channels, kernel_size=3, padding=1)
+ self.conv5 = nn.Conv2d(self.nb_channels, self.nb_channels, kernel_size=3, padding=1)
+ self.fc1 = nn.Linear(16 * self.nb_channels, 512)