gnadaf:

outputs are calculated in forward pass, and layer weights and bias are intermediate results.


The weight and bias would be parameters and I wouldn’t call them intermediate results.
I think the intermediate activations could be called intermediate results, but I’m still unsure if that’s really what you are looking for as I haven’t heard this naming so far.
By intermediate activations I mean e.g.:
def forward(self, x):
    intermediate_act1 = self.layer1(x)
    intermediate_act2 = self.layer2(intermediate_act1)
    ...