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.")