I’m creating a class, details are not so important just the fact that in init there are conv layers and nn.Parameters:
class MyClass(nn.Module):
    def __init__(self, args):
        super(MyClass, self).__init__()
        nc = 100
        self.teta0 = nn.Parameter(torch.cuda.FloatTensor(1,nc),requires_grad=True)
        self.teta1 = nn.Parameter(torch.cuda.FloatTensor(1,nc),requires_grad=True)
        self.teta2 = nn.Parameter(torch.cuda.FloatTensor(1,nc),requires_grad=True)
        self.conv  = nn.Conv2d(1,3,3)
    def forward(self,a,b): 
        first  = self.teta2*(a-self.teta1)
         ....
        return loss

Now I’m instantiating the class and print
        self.model= MyClass(args)
        print(self.model)

I’m getting:

MyClass (
(conv): Conv2d(1, 3, kernel_size=(3, 3), stride=(1, 1))
)

It’s seems like the class is not consisting of those nn.Parameters.
Just to makes things clear, self.conv is there because I had this problem and I wanted to see if the conv layer can be seen.
Any idea what’s going on, where I’m mistaking and what can lead to such an error?
Thanks!