inceotionblock.py

class Inception_block(nn.Module):
    def __init__(self, in_channels, out_1x1, red_3x3, out_3x3, red_5x5, out_5x5, out_1x1pool):
        super(Inception_block, self).__init__()
        self.branch1 = conv_block(in_channels, out_1x1, kernel_size=(1,1))
        
        self.branch2 = nn.Sequential(
            conv_block(in_channels, red_3x3, kernel_size=(1,1)),
            conv_block(red_3x3, out_3x3, kernel_size=(3,3),padding=(1,1))
            )
        
        self.branch3 = nn.Sequential(
            conv_block(in_channels, red_5x5, kernel_size=(1,1)),
            conv_block(red_5x5, out_5x5, kernel_size=(5,5),padding=(2,2))
            )
    
        self.branch4 = nn.Sequential(
            nn.MaxPool2d(kernel_size=(3,3),stride=(1,1),padding=(1,1)),
            conv_block(in_channels,out_1x1pool,kernel_size=(1,1))
            )
    
    def forward(self, x):
        return torch.cat([self.branch1(x), self.branch2(x), self.branch3(x), self.branch4(x)], 1)