Spaces:
Sleeping
Sleeping
File size: 1,924 Bytes
46b0409 0f41753 46b0409 0f41753 46b0409 0f41753 46b0409 0f41753 46b0409 0f41753 46b0409 0f41753 46b0409 0f41753 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
import argparse
import os
import multiprocessing
import random
# argument parsing
parser = argparse.ArgumentParser(description="Run parameter tests for MC agent")
parser.add_argument(
"--env",
type=str,
default="Taxi-v3",
help="environment to run",
)
parser.add_argument(
"--num_tests",
type=int,
default=25,
help="number of tests to run for each parameter combination",
)
parser.add_argument(
"--wandb_project",
type=str,
default=None,
help="wandb project name to log to",
)
args = parser.parse_args()
env, num_tests, wandb_project = args.env, args.num_tests, args.wandb_project
agent = "MCAgent"
vals_update_type = [
"first_visit"
] # Note: Every visit takes too long due to these environment's reward structure
vals_gamma = [1.0, 0.98, 0.96, 0.94]
vals_epsilon = [0.1, 0.2, 0.3, 0.4, 0.5]
# vals_gamma = [1.0]
# vals_epsilon = [0.5]
if env == "CliffWalking-v0":
n_train_episodes = 2500
max_steps = 200
elif env == "FrozenLake-v1":
n_train_episodes = 5000
max_steps = 200
elif env == "Taxi-v3":
n_train_episodes = 10000
max_steps = 500
else:
raise ValueError(f"Unsupported environment: {env}")
def run_test(args):
command = f"python3 run.py --train --agent {agent} --env {env}"
command += f" --n_train_episodes {n_train_episodes} --max_steps {max_steps}"
command += f" --gamma {args[0]} --epsilon {args[1]} --update_type {args[2]}"
command += f" --run_name_suffix {args[3]}"
if wandb_project is not None:
command += f" --wandb_project {wandb_project}"
command += " --no_save"
os.system(command)
with multiprocessing.Pool(8) as p:
tests = []
for update_type in vals_update_type:
for gamma in vals_gamma:
for eps in vals_epsilon:
tests.extend((gamma, eps, update_type, i) for i in range(num_tests))
random.shuffle(tests)
p.map(run_test, tests)
|