def make_env():
env_config = {
"bag_capacity": 63,
'item_sizes': [1, 2, 3, 4, 5, 6, 7, 8, 9],
# 'item_probabilities': [0.14, 0.10, 0.06, 0.13, 0.11, 0.13, 0.03, 0.11, 0.19], #bounded waste
'item_probabilities': [0.06, 0.11, 0.11, 0.22, 0, 0.11, 0.06, 0,
0.33], # perfect pack
# 'item_probabilities': [0, 0, 0, 1/3, 0, 0, 0, 0, 2/3], #linear waste
'time_horizon': 1000, # 10000
}
env = BinPackingActionMaskGymEnvironment(env_config)
return env
def make_env(env_name, agent, seed=-1, render_mode=False):
# env = CarRacingDream(agent)
# if seed <0:
# seed = np.random.randint(2**31-1)
# env.seed(seed)
#
# return env
env_config = {
"bag_capacity": 63,
'item_sizes': [1, 2, 3, 4, 5, 6, 7, 8, 9],
# 'item_probabilities': [0.14, 0.10, 0.06, 0.13, 0.11, 0.13, 0.03, 0.11, 0.19], #bounded waste
'item_probabilities': [0.06, 0.11, 0.11, 0.22, 0, 0.11, 0.06, 0,
0.33], # perfect pack
# 'item_probabilities': [0, 0, 0, 1/3, 0, 0, 0, 0, 2/3], #linear waste
'time_horizon': 1000, # 10000
}
env = BinPackingActionMaskGymEnvironment(env_config)
return env
print(action)
return [action]
env_config = {
"bag_capacity": 63,
'item_sizes': [1, 2, 3, 4, 5, 6, 7, 8, 9],
# 'item_probabilities': [0.14, 0.10, 0.06, 0.13, 0.11, 0.13, 0.03, 0.11, 0.19], #bounded waste
'item_probabilities': [0.06, 0.11, 0.11, 0.22, 0, 0.11, 0.06, 0,
0.33], #perfect pack
# 'item_probabilities': [0, 0, 0, 1/3, 0, 0, 0, 0, 2/3], #linear waste
'time_horizon': 1000, # 10000
}
env = BinPackingActionMaskGymEnvironment(env_config)
state = env.reset()
done = False
total_reward = 0
while not done:
print([x[0] for x in state[0]])
print(np.shape(state))
# action = get_action(state)
action = get_human_action()
print(action)
state, reward, done, info = env.step(action)
print("reward", reward)
total_reward += reward
print("Total reward for best fit baseline agent: ", total_reward)
def register_env_creator(self):
from bin_packing_environment import BinPackingActionMaskGymEnvironment
register_env(
"BinPackingActionMaskGymEnvironment-v1",
lambda env_config: BinPackingActionMaskGymEnvironment(env_config))