def sample(self):
    ' Returns a array with one sample from each discrete action space '
    np_random = np.random.RandomState()
    random_array = np_random.rand(self.num_discrete_space)
    return [int(x) for x in np.floor((np.multiply(((self.high - self.low) + 1.0), random_array) + self.low))]
Returns a array with one sample from each discrete action space
def sample(self):
    '  '
    np_random = np.random.RandomState()
    random_array = np_random.rand(self.num_discrete_space)
    return [int(x) for x in np.floor((np.multiply(((self.high - self.low) + 1.0), random_array) + self.low))]