I try to compare different CNN models. I use Keras and for training, I use a GPU, Google Colab with Tensorflow backend. Unfortunately I'm not able to create the same initial conditions for the CNNs (or in other words: I always get different results). Although by putting the following lines at the top of the code, I get always different results after every run.
from numpy.random import seed seed(1) from tensorflow import set_random_seed set_random_seed(2)
Can it be that it is simply not possible to get reproducible results?
Would it be the best way to simply repeat the training several times and then either calculate a mean (if possible) or simply practice ensemble learning? All without using seeds or random_states or shuffle=False etc.
What would be the best way to compare these models?