I am looking through some example code, and am not new to Machine Learning, but I saw:
self.fc_mu = nn.Linear(hidden_size, hidden_size)
self.fc_sigma = nn.Linear(hidden_size, hidden_size)
I understand that self.fc1(),self.fc2()… are referring to the fully connected layers one and two which are both Linear in my example, but what is self.fc_mu referring to, and what does it return? Also, what are the parameters of self.fc_mu(), and self.fc_sigma() which I saw used many times? Thank you in advance, I am just struggling to figure this out.