Hi there!
I’m working through some Udacity courses on PyTorch and decided to go the extra mile to extend the nn.Sequential class. I wanted to automate defining each layer’s activations by just passing a tuple containing the number of nodes in each class.
So normally if I wanted to perform a forward pass with an already initialized nn.Sequential model, I’d simply use
out = model(x)
# OR
out = model.forward(x)

Now that I’ve extended the class, I am trying to use
out = self(x)
# OR
out = self.forward(x)

and am getting the following error:
TypeError: forward() missing 1 required positional argument: 'target'

I’ve done nothing to alter the forward method at all, so I’m quite confused. I’d appreciate any help. Thank you!
The full code for my class is below:
class Network(nn.Sequential):
    def __init__(self, layers):
        super().__init__(self.init_modules(layers))
        self.criterion = nn.NLLLoss()
        self.optimizer = optim.Adam(self.parameters(), lr=0.003)


    def train(self, trainloader, epochs):
        for e in range(epochs):
            for x, y in trainloader:
                x = x.view(x.shape[0], -1)
                self.optimizer.zero_grad()
                loss = self.criterion(self(x), y)
                loss.backward()
                self.optimizer.step()

    def init_modules(self, layers):
        # Logic unimportant to the question (I think)