I have 3 neural networks, A, B, C.
A and B have different architecture, but I want C to have same architecture as B, but different weights, bias initialization, and its parameters to be updated differently.
If I do
C = B
then it would mean both are same neural network with parameters getting updated in same way.
how do I ensure that both have different parameters but same architecture?