import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--smoke-test",
action="store_true",
default=False,
help="Finish quickly for training.")
args = parser.parse_args()
# Get path of this very script to look for yaml files.
abs_yaml_path = Path(__file__).parent
print("abs_yaml_path={}".format(abs_yaml_path))
yaml_files = 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,
max_num_repeats=1,
smoke_test=args.smoke_test,
)
test_output_json = os.environ.get("TEST_OUTPUT_JSON",
"/tmp/rllib_stress_tests.json")
with open(test_output_json, "wt") as f:
json.dump(results, f)
print("Ok.")
"""Multi-GPU learning tests for RLlib (torch and tf).
"""
import json
import os
from pathlib import Path
from ray.rllib.utils.test_utils import run_learning_tests_from_yaml
if __name__ == "__main__":
# Get path of this very script to look for yaml files.
abs_yaml_path = Path(__file__).parent
print("abs_yaml_path={}".format(abs_yaml_path))
yaml_files = 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)
test_output_json = os.environ.get(
"TEST_OUTPUT_JSON", "/tmp/rllib_multi_gpu_learning_tests.json")
with open(test_output_json, "wt") as f:
json.dump(results, f)
print("Ok.")
parser = argparse.ArgumentParser()
parser.add_argument("--smoke-test",
action="store_true",
default=False,
help="Finish quickly for training.")
args = parser.parse_args()
if __name__ == "__main__":
# Get path of this very script to look for yaml files.
abs_yaml_path = Path(__file__).parent
print("abs_yaml_path={}".format(abs_yaml_path))
# This pattern match is kind of hacky. Avoids cluster.yaml to get sucked
# into this.
yaml_files = abs_yaml_path.rglob("*test*.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,
smoke_test=args.smoke_test,
)
test_output_json = os.environ.get("TEST_OUTPUT_JSON",
"/tmp/rllib_learning_test.json")
with open(test_output_json, "wt") as f:
json.dump(results, f)
print("PASSED.")
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.")