def test_episodes_reproducible():
num_dcs = 5
num_customers = 2 # scale up to 200
num_commodities = 10 # scale up to 50
orders_per_day = 2 # was going to be 0.1 but ran too slow.
# orders_per_day = 2
dcs_per_customer = 2
demand_mean = 500
demand_var = 150
num_steps = 10 # 1 month
# num_episodes = 500
num_episodes = 1
reproducibility.set_seeds(0)
runner_donothing_1 = experiment_runner.create_donothing_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_donothing_1.run_episodes(
num_steps,
num_episodes,
orders_per_day,
experiment_name=f"donothing_reproducible_test_1")
reproducibility.set_seeds(0)
runner_donothing_2 = experiment_runner.create_donothing_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
runner_donothing_2.run_episodes(
num_steps,
num_episodes,
orders_per_day,
experiment_name=f"donothing_reproducible_test_2")
a = pd.read_csv(
"data/results/donothing_reproducible_test_1/ep_0/movement_detail_report.csv"
)[['source_name', 'destination_name']]
b = pd.read_csv(
"data/results/donothing_reproducible_test_2/ep_0/movement_detail_report.csv"
)[['source_name', 'destination_name']]
compare = pd.concat([a, b], axis=1)
compare.columns = ['s1', 'd1', 's2', 'd2']
print(compare)
print("Equality: ", a.equals(b))
assert a.equals(b)
def run_agent_66_custom_agent():
print("===RUNNING agent66===")
reproducibility.set_seeds(0)
print("Check this array to ensure reproducibility")
print("Reproducibility agent66", np.random.randint(0, 500, size=(5, 1)))
runner_bestfit = experiment_runner.create_agent_66_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_bestfit.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name=f"z_debug_agent_highest")
print("===DONE agent66===")
def run_bestfit():
print("===RUNNING BESTFIT===")
reproducibility.set_seeds(0)
print("Check this array to ensure reproducibility")
print("Reproducibility BESTFIT", np.random.randint(0, 500, size=(5, 1)))
runner_bestfit = experiment_runner.create_bestfit_experiment_runner(
num_dcs, num_customers, dcs_per_customer, demand_mean, demand_var,
num_commodities, orders_per_day, num_steps)
runner_bestfit.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name=f"bestfit_few_warehouses_v3")
print("===DONE BESTFIT===")
def run_donothing():
print("!!!RUNNING donothing!!!")
reproducibility.set_seeds(0)
print("Check this array to ensure reproducibility")
print("Reproducibility donothing", np.random.randint(0, 500, size=(5, 1)))
runner_donothing = experiment_runner.create_donothing_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
runner_donothing.run_episodes(
num_steps,
num_episodes,
orders_per_day,
experiment_name=f"donotrhing_few_warehouses_v3")
print("!!!DONE donothing!!!")
def run_random():
print("***RUNNING RANDOM***")
reproducibility.set_seeds(0)
print("Check this array to ensure reproducibility")
print("Reproducibility RANDOM", np.random.randint(0, 500, size=(5, 1)))
runner_random = experiment_runner.create_random_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
runner_random.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name=f"dumb_few_warehouses_v3")
print("***DONE RANDOM***")
def run_dqn():
print("!!!RUNNING DQN!!!")
reproducibility.set_seeds(0)
print("Check this array to ensure reproducibility")
print("Reproducibility DQN", np.random.randint(0, 500, size=(5, 1)))
runner_dqn = experiment_runner.create_dqn_experiment_runner(
num_dcs,
num_customers,
dcs_per_customer,
demand_mean,
demand_var,
num_commodities,
orders_per_day,
num_steps,
)
runner_dqn.run_episodes(num_steps,
num_episodes,
orders_per_day,
experiment_name=f"dqn2_few_warehouses_v3")
runner_dqn.agent.save_weights("models/dqn2_few_warehouses_v3.h5")
print("!!!DONE DQN!!!")