from pathlib import Path
from dacbench.agents import RandomAgent
from dacbench.logger import Logger
from dacbench.runner import run_benchmark
from dacbench.benchmarks import CMAESBenchmark
from dacbench.wrappers import StateTrackingWrapper
# Make CMAESBenchmark environment
bench = CMAESBenchmark()
env = bench.get_environment()
# Make Logger object to track state information
logger = Logger(experiment_name=type(bench).__name__,
output_path=Path("../plotting/data"))
logger.set_env(env)
# Wrap env with StateTrackingWrapper
env = StateTrackingWrapper(env, logger=logger.add_module(StateTrackingWrapper))
# Run random agent for 5 episodes and log state information to file
# You can plot these results with the plotting examples
agent = RandomAgent(env)
run_benchmark(env, agent, 5, logger=logger)
logger.close()
def test_logging_discrete(self):
temp_dir = tempfile.TemporaryDirectory()
seed = 0
logger = Logger(
output_path=Path(temp_dir.name),
experiment_name="test_discrete_logging",
step_write_frequency=None,
episode_write_frequency=1,
)
bench = LubyBenchmark()
bench.set_seed(seed)
env = bench.get_environment()
env.seed_action_space(seed)
action_logger = logger.add_module(ActionFrequencyWrapper)
wrapped = ActionFrequencyWrapper(env, logger=action_logger)
agent = RandomAgent(env)
logger.set_env(env)
run_benchmark(wrapped, agent, 10, logger)
action_logger.close()
logs = load_logs(action_logger.get_logfile())
dataframe = log2dataframe(logs, wide=True)
expected_actions = [
0,
3,
5,
4,
3,
5,
5,
5,
3,
3,
2,
1,
0,
1,
2,
0,
1,
1,
0,
1,
2,
4,
3,
0,
1,
3,
0,
3,
3,
3,
4,
4,
4,
5,
4,
0,
4,
2,
1,
3,
4,
2,
1,
3,
3,
2,
0,
5,
2,
5,
2,
1,
5,
3,
2,
5,
1,
0,
2,
3,
1,
3,
2,
3,
2,
4,
3,
4,
0,
5,
5,
1,
5,
0,
1,
5,
5,
3,
3,
2,
]
self.assertListEqual(dataframe.action.to_list(), expected_actions)
temp_dir.cleanup()
def test_logging_multi_discrete(self):
temp_dir = tempfile.TemporaryDirectory()
seed = 0
logger = Logger(
output_path=Path(temp_dir.name),
experiment_name="test_multi_discrete_logging",
step_write_frequency=None,
episode_write_frequency=1,
)
bench = ModeaBenchmark()
bench.set_seed(seed)
env = bench.get_environment()
env.seed_action_space(seed)
action_logger = logger.add_module(ActionFrequencyWrapper)
wrapped = ActionFrequencyWrapper(env, logger=action_logger)
agent = RandomAgent(env)
logger.set_env(env)
run_benchmark(wrapped, agent, 1, logger)
action_logger.close()
logs = load_logs(action_logger.get_logfile())
dataframe = log2dataframe(logs, wide=True)
expected_actions = pd.DataFrame({
"action_0": {
0: 0,
1: 1,
2: 0,
3: 1,
4: 1,
5: 0,
6: 1,
7: 1,
8: 0,
9: 0,
10: 0,
},
"action_1": {
0: 1,
1: 0,
2: 1,
3: 0,
4: 0,
5: 1,
6: 0,
7: 1,
8: 0,
9: 0,
10: 1,
},
"action_10": {
0: 0,
1: 0,
2: 1,
3: 0,
4: 0,
5: 0,
6: 0,
7: 2,
8: 1,
9: 2,
10: 1,
},
"action_2": {
0: 1,
1: 1,
2: 1,
3: 0,
4: 1,
5: 1,
6: 1,
7: 1,
8: 0,
9: 0,
10: 1,
},
"action_3": {
0: 0,
1: 1,
2: 1,
3: 1,
4: 1,
5: 1,
6: 1,
7: 0,
8: 0,
9: 1,
10: 1,
},
"action_4": {
0: 0,
1: 1,
2: 1,
3: 0,
4: 1,
5: 0,
6: 0,
7: 1,
8: 0,
9: 1,
10: 0,
},
"action_5": {
0: 1,
1: 0,
2: 0,
3: 0,
4: 1,
5: 1,
6: 1,
7: 0,
8: 0,
9: 0,
10: 1,
},
"action_6": {
0: 0,
1: 1,
2: 1,
3: 0,
4: 0,
5: 0,
6: 0,
7: 0,
8: 1,
9: 0,
10: 0,
},
"action_7": {
0: 1,
1: 0,
2: 0,
3: 0,
4: 0,
5: 0,
6: 0,
7: 1,
8: 1,
9: 1,
10: 0,
},
"action_8": {
0: 0,
1: 1,
2: 0,
3: 1,
4: 1,
5: 1,
6: 0,
7: 1,
8: 0,
9: 0,
10: 1,
},
"action_9": {
0: 1,
1: 2,
2: 1,
3: 0,
4: 0,
5: 1,
6: 1,
7: 1,
8: 2,
9: 0,
10: 2,
},
})
for column in expected_actions.columns:
# todo: seems to be an bug here. Every so ofter the last action is missing.
# Double checked not a logging problem. Could be a seeding issue
self.assertListEqual(
dataframe[column].to_list()[:10],
expected_actions[column].to_list()[:10],
f"Column {column}",
)
temp_dir.cleanup()
def make_agent(env):
return RandomAgent(env)