Results not reproducible with Keras and TensorFlow in Python

Question

I have the problem, that I am not able to reproduce my results with Keras and ThensorFlow.

It seems like recently there has been a workaround published on the Keras

Answer 1

My answer is the following, which uses Keras with Tensorflow as backend. Within your nested for loop, where one typically iterates through the various parameters you wish to explore for your model's development, immediately add this function after your last for loop.

for...
   for...
      reset_keras()
      .
      .
      .

where the reset function is defined as

def reset_keras():
    sess = tf.keras.backend.get_session()
    tf.keras.backend.clear_session()
    sess.close()
    sess = tf.keras.backend.get_session()
    np.random.seed(1)
    tf.set_random_seed(2)

PS: The function above also actually avoids your nvidia GPU from building up too much memory (which happens after many iteration) so that it eventually becomes very slow...so the function restores GPU performance and maintains results as reproducible.