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 = """
