check_baseline.py

from env import SchedulingEnv
import gym
from stable_baselines3.common.env_checker import check_env
from stable_baselines3 import A2C, DDPG, DQN, TD3
import argparse
import numpy as np

np.random.seed(2)

def parse_arguments():
    ap = argparse.ArgumentParser()
    ap.add_argument("-n", "--numQueues", default=3,
                    help="number of queues", type=int)
    ap.add_argument("-b", "--boost", default=0,
                    help="", type=int)
    return ap

arg_parser = parse_arguments()
args = vars(arg_parser.parse_args())
env = SchedulingEnv(args["boost"], args["numQueues"], False)
print("Agent: Baseline")

# bound on iterations = 100000
for i in range(100):
    obs = env.reset()
    init_quantum = env.quantum_list
    r= 0
    for j in range(10000):
        obs, reward, done, info = env.step(init_quantum)
        r += reward
        if done:
            break 
    print (f"Iteration {i}: reward = ", r)
    env.print_stats()
    print("---------------------------------------------------------------------------------------")
# env.render()