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add in_cluster option for KubernetesScheduler #917

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add in_cluster option for KubernetesScheduler #917

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26 changes: 22 additions & 4 deletions torchx/schedulers/kubernetes_scheduler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -446,6 +446,7 @@ class KubernetesOpts(TypedDict, total=False):
image_repo: Optional[str]
service_account: Optional[str]
priority_class: Optional[str]
in_cluster: Optional[bool]


class KubernetesScheduler(DockerWorkspaceMixin, Scheduler[KubernetesOpts]):
Expand Down Expand Up @@ -553,10 +554,16 @@ def _api_client(self) -> "ApiClient":
c = self._client
if c is None:
configuration = client.Configuration()
try:
config.load_kube_config(client_configuration=configuration)
except config.ConfigException as e:
warnings.warn(f"failed to load kube config: {e}")
if self._in_cluster:
try:
config.load_incluster_config(client_configuration=configuration)
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Is there a way to automatically detect this? Maybe we should try the kube_config and then this if KubeConfig doesn't exist via a try-except?

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Ok, will try to add it

except config.ConfigException as e:
warnings.warn(f"failed to load incluster config: {e}")
else:
try:
config.load_kube_config(client_configuration=configuration)
except config.ConfigException as e:
warnings.warn(f"failed to load kube config: {e}")

c = self._client = client.ApiClient(configuration)

Expand Down Expand Up @@ -586,6 +593,12 @@ def schedule(self, dryrun_info: AppDryRunInfo[KubernetesJob]) -> str:
cfg = dryrun_info._cfg
assert cfg is not None, f"{dryrun_info} missing cfg"
namespace = cfg.get("namespace") or "default"

in_cluster = cfg.get("in_cluster") or False
if not isinstance(in_cluster, bool):
raise TypeError(f"config value 'in_cluster' must be a bool, got {in_cluster}")

self._in_cluster = in_cluster

images_to_push = dryrun_info.request.images_to_push
self.push_images(images_to_push)
Expand Down Expand Up @@ -675,6 +688,11 @@ def _run_opts(self) -> runopts:
type_=str,
help="The name of the PriorityClass to set on the job specs",
)
opts.add(
"in_cluster",
type_=bool,
help="Type of run to use local cluster if KUBECONFIG not provided"
)
return opts

def describe(self, app_id: str) -> Optional[DescribeAppResponse]:
Expand Down
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