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[SDK] Add env & env_from in client tune #2235

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merged 2 commits into from
Nov 17, 2023
Merged

[SDK] Add env & env_from in client tune #2235

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18d522a
add env & env_from spec
shipengcheng1230 Oct 18, 2023
3e552cf
unify env and env_from specs
shipengcheng1230 Nov 1, 2023
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18 changes: 18 additions & 0 deletions sdk/python/v1beta1/kubeflow/katib/api/katib_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -140,6 +140,7 @@ def tune(
parameters: Dict[str, Any],
base_image: str = constants.BASE_IMAGE_TENSORFLOW,
namespace: Optional[str] = None,
env_per_trial: Optional[Union[Dict[str, str], List[Union[client.V1EnvVar, client.V1EnvFromSource]]]] = None,
algorithm_name: str = "random",
algorithm_settings: Union[dict, List[models.V1beta1AlgorithmSetting], None] = None,
objective_metric_name: str = None,
Expand Down Expand Up @@ -172,6 +173,12 @@ def tune(
objective function.
base_image: Image to use when executing the objective function.
namespace: Namespace for the Experiment.
env_per_trial: Environment variable(s) to be attached to each trial container.
You can specify a dictionary as a mapping object representing the environment variables.
Otherwise, you can specify a list, in which the element can either be a kubernetes.client.models.V1EnvVar (documented here:
https://github.com/kubernetes-client/python/blob/master/kubernetes/docs/V1EnvVar.md)
or a kubernetes.client.models.V1EnvFromSource (documented here:
https://github.com/kubernetes-client/python/blob/master/kubernetes/docs/V1EnvFromSource.md)
algorithm_name: Search algorithm for the HyperParameter tuning.
algorithm_settings: Settings for the search algorithm given.
For available fields, check this doc: https://www.kubeflow.org/docs/components/katib/experiment/#search-algorithms-in-detail.
Expand Down Expand Up @@ -318,6 +325,15 @@ def tune(
requests=resources_per_trial,
limits=resources_per_trial,
)

if isinstance(env_per_trial, dict):
env, env_from = [client.V1EnvVar(name=str(k), value=str(v)) for k, v in env_per_trial.items()] or None, None

if env_per_trial:
env = [x for x in env_per_trial if isinstance(x, client.V1EnvVar)] or None
env_from = [x for x in env_per_trial if isinstance(x, client.V1EnvFromSource)] or None
else:
env, env_from = None, None

# Create Trial specification.
trial_spec = client.V1Job(
Expand All @@ -336,6 +352,8 @@ def tune(
image=base_image,
command=["bash", "-c"],
args=[exec_script],
env=env,
env_from=env_from,
resources=resources_per_trial,
)
],
Expand Down