I have my own network. But it is giving me different outputs each time I run the code. I'm using keras (with Tensorflow backend), write the following code for reproducibility. My training sample: 280, validation sample # 27, test sample # 21.
# The following lines are for reproducibility
import os
import random as rn
os.environ['PYTHONHASHSEED'] = '0'
# random seed for NP genreator of ranodm numbers
np.random.seed(37)
rn.seed(1254) # specifying the seed for python-generated random numbers:
import tensorflow as tf
tf.compat.v1.set_random_seed(89) #tf.set_random_seed(89)
import keras.backend.tensorflow_backend as K
session_conf = tf.compat.v1.ConfigProto(intra_op_parallelism_threads=1, inter_op_parallelism_threads=1)
sess=tf.compat.v1.Session(graph=tf.compat.v1.get_default_graph(), config= session_conf)
K.set_session(sess)
