If Keras results are not reproducible, what's the best practice for comparing models and choosing hyper parameters?

Question

UPDATE: This question was for Tensorflow 1.x. I upgraded to 2.0 and (at least on the simple code below) the reproducibility issue seems fixed on 2.0. So that solves my p

Answer 1

Putting only the code of below, it works. The KEY of the question, VERY IMPORTANT, is to call the function reset_seeds() every time before running the model. Doing that you will obtain reproducible results as I checked in the Google Collab.

import numpy as np
import tensorflow as tf
import random as python_random

def reset_seeds():
   np.random.seed(123) 
   python_random.seed(123)
   tf.random.set_seed(1234)

reset_seeds()