def setUp(self): ray.init(num_cpus=1, num_gpus=0, local_mode=True) tmpdir = tempfile.mkdtemp() test_name = "TuneRestoreTest" tune.run( "PG", name=test_name, stop={"training_iteration": 1}, checkpoint_freq=1, local_dir=tmpdir, config={ "env": "CartPole-v0", }, ) logdir = os.path.expanduser(os.path.join(tmpdir, test_name)) self.logdir = logdir self.checkpoint_path = recursive_fnmatch(logdir, "checkpoint-1")[0]
from ray.autoscaler._private.azure.config import (_configure_key_pair as _azure_configure_key_pair) from ray.autoscaler._private.gcp import config as gcp_config from ray.autoscaler._private.local import config as local_config from ray.autoscaler._private.util import prepare_config, validate_config,\ _get_default_config, merge_setup_commands from ray.autoscaler._private.providers import _NODE_PROVIDERS from ray.autoscaler._private._kubernetes.node_provider import\ KubernetesNodeProvider from ray.autoscaler.tags import NODE_TYPE_LEGACY_HEAD, NODE_TYPE_LEGACY_WORKER from ray.test_utils import load_test_config, recursive_fnmatch RAY_PATH = os.path.abspath(os.path.dirname(os.path.dirname(__file__))) CONFIG_PATHS = recursive_fnmatch(os.path.join(RAY_PATH, "autoscaler"), "*.yaml") CONFIG_PATHS += recursive_fnmatch(os.path.join(RAY_PATH, "tune", "examples"), "*.yaml") def ignore_k8s_operator_configs(paths): return [ path for path in paths if "kubernetes/operator_configs" not in path and "kubernetes/job-example.yaml" not in path ] CONFIG_PATHS = ignore_k8s_operator_configs(CONFIG_PATHS) EXPECTED_LOCAL_CONFIG_STR = """