ray/release/rllib_tests/learning_tests/run.py

57 lines
1.6 KiB
Python

"""Learning regression tests for RLlib (torch and tf).
Runs Atari/PyBullet benchmarks for all major algorithms.
"""
import json
import os
from pathlib import Path
from ray.rllib.utils.test_utils import run_learning_tests_from_yaml
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"--smoke-test",
action="store_true",
default=False,
help="Finish quickly for training.",
)
parser.add_argument(
"--yaml-sub-dir",
type=str,
default="",
help="Sub directory under yaml_files/ to look for test files.",
)
args = parser.parse_args()
assert args.yaml_sub_dir, "--yaml-sub-dir can't be empty."
# Get path of this very script to look for yaml files.
abs_yaml_path = os.path.join(
str(Path(__file__).parent), "yaml_files", args.yaml_sub_dir
)
print("abs_yaml_path={}".format(abs_yaml_path))
yaml_files = Path(abs_yaml_path).rglob("*.yaml")
yaml_files = sorted(
map(lambda path: str(path.absolute()), yaml_files), reverse=True
)
# Run all tests in the found yaml files.
results = run_learning_tests_from_yaml(
yaml_files=yaml_files,
# Note(jungong) : run learning tests to full desired duration
# for performance regression purpose.
# Talk to jungong@ if you have questions about why we do this.
use_pass_criteria_as_stop=False,
smoke_test=args.smoke_test,
)
test_output_json = os.environ.get("TEST_OUTPUT_JSON", "/tmp/learning_test.json")
with open(test_output_json, "wt") as f:
json.dump(results, f)
print("Ok.")