def run_model(params):
# https://stackoverflow.com/questions/11526975/set-random-seed-programwide-in-python
# https://stackoverflow.com/questions/30517513/global-seed-for-multiple-numpy-imports
random.seed(params.seed)
np.random.seed(params.seed)
# Must be called before Session
# https://stackoverflow.com/questions/38469632/tensorflow-non-repeatable-results/40247201#40247201
tf.set_random_seed(params.seed)
qagent = QAgent(params)
if params.is_train:
qagent.fit()
elif params.eval_mode == 0:
qagent.evaluate_mine()
elif params.eval_mode == 1:
qagent.test_mine()
elif params.eval_mode == 2:
for mines in range(1, 13):
params.mines_min = mines
params.mines_max = mines
print("Mines =", mines)
qagent.test_mine()
tf.reset_default_graph()
qagent = QAgent(params)
def train(params):
# https://stackoverflow.com/questions/11526975/set-random-seed-programwide-in-python
# https://stackoverflow.com/questions/30517513/global-seed-for-multiple-numpy-imports
random.seed(params.seed)
np.random.seed(params.seed)
# Must be called before Session
# https://stackoverflow.com/questions/38469632/tensorflow-non-repeatable-results/40247201#40247201
tf.set_random_seed(params.seed)
qagent = QAgent(params)
if params.is_train:
qagent.fit()
else:
qagent.evaluate_mine()