Hello,
would you know how I can adapt this code so that sizes of tensors must match because I have this error: x = torch.cat([x1,x2],1) RuntimeError: Sizes of tensors must match except in dimension 0. Got 32 and 1 (The offending index is 0).
My images are size 416x416.
Thank you in advance for your help,
num_classes = 20
class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
                
        self.inc = models.inception_v3(pretrained=True)
        self.inc.aux_logits = False

        for child in list(self.inc.children())[:-5]:
            for param in child.parameters():
                param.requires_grad = False

        self.inc.fc = nn.Sequential()
                    
        self.dens121 = models.densenet121(pretrained=True)

        for child in list(self.dens121.children())[:-6]:
            for param in child.parameters():
                param.requires_grad = False

        self.dens121 = nn.Sequential(*list(self.dens121.children())[:-1])
           
        self.SiLU = nn.SiLU()      
        self.linear = nn.Linear(4096, num_classes)
        self.dropout = nn.Dropout(0.2)
        
    def forward(self, x):
        x1 = self.SiLU(self.dens121(x))
        x1 = x1.view(-1, 2048)
        
        x2 = self.inc(x).view(-1, 2048)
        x = torch.cat([x1,x2],1)

        return self.linear(self.dropout(x))