How do I make my neural network learn same pattern multiple times, that is one neural network learns minor modifications of the same pattern, and stores them in a list, and returns this list to another neural network?
if I do something like this,
class Model(nn.Module):
def __init__(self):
self.lin = nn.Linear(3, 3)
def forward(self, x):
out = self.lin(x)
return out, out
then it would return two outputs, but both of them would be same, I want redundancy, but not exactly same patterns, only minor modifications.