How to print the constant numbers in the forward function

hello, guys. I only have access to a well-trained model and have forgot the exact settings in the Network strucutre.

I used to train a model with a layer like this:

def forward(self, x):
    x_a = self.linear_a(x)
    x_b = self.linear_b(x)
    x_c = self.linear_c(x)
    s_a = self.score_a(x)
    s_b = self.score_b(x)
    s_c = self.score_c(x)

    s_a = torch.sigmoid(s_a)
    s_b = torch.sigmoid(s_b)
    s_c = torch.sigmoid(s_c)

    f_a = x_a
    f_b =[(s_a+0.5)*x_a, (s_b+0.5)*x_b], 1)
    f_c =[(s_a+0.5)*x_a, (s_b+0.5)*x_b, (s_c)*x_c], 1)
    return [f_a, f_b, f_c, f_c]

You can see that I use some constant number here like "f_b =[(s_a+0.5)*x_a, (s_b+0.5)*x_b], 1)"and I have forgot the exact value of these numbers. But I have stored a model and I am wondering how can I print the numbers within the equation “f_b =[(s_a+0.5)*x_a, (s_b+0.5)*x_b], 1),1)”

Did you save your model’s state_dict?
If so, I think there isn’t an option to get the constants in this line, since they weren’t saved and just defined in the forward pass.

Thanks for your comments.