def get_action(self, state):
    if (np.random.rand() < self.epsilon):
        return random.randint(0, 3)
    predicted_actions = self.model.predict([tf.expand_dims(state[0], axis=0), tf.expand_dims(state[1], axis=0)])
    return np.argmax(predicted_actions[0])
def get_action(self, state):
    if (np.random.rand() < self.epsilon):
        return random.randint(0, 3)
    predicted_actions = self.model.predict([tf.expand_dims(state[0], axis=0), tf.expand_dims(state[1], axis=0)])
    return np.argmax(predicted_actions[0])