You have a few typos in your model definition, e.g. __int__ instead of __init__, which is why your layers won’t be initialized and your parameters are empty.
Also, some layers have types, e.g. nn.maxpoo2d instead of nn.MaxPool2d.
After fixing these issue, you’ll get other errors, since self.hidden and self.out currently don’t get any input.
Here is a fixed version:
class NeuralNet(nn.Module):
    def __init__(self):
        super(NeuralNet, self).__init__()
        self.conv = nn.Conv2d(1, 28, kernel_size=(3, 3))
        self.pool = nn.MaxPool2d(2, 2)
        self.hidden = nn.Linear(28*13*13, 128)
        self.drop = nn.Dropout(0.2)
        self.out = nn.Linear(128, 10)  # fully connected layer
        self.act = nn.ReLU()

    def forward(self, x):
        x = self.act(self.conv(x))
        print(x.size())
        x = self.pool(x)
        x = x.view(x.size(0), -1)
        x = self.act(self.hidden(x))
        x = self.drop(x)
        x = self.out(x)
        return x