SweepJobLimits Class

Limits for Sweep Jobs.

Inheritance

azure.ai.ml.entities._job.job_limits.JobLimits

SweepJobLimits

Constructor

SweepJobLimits(*, max_concurrent_trials: int | None = None, max_total_trials: int | None = None, timeout: int | None = None, trial_timeout: int | str | None = None)

Keyword-Only Parameters

Name	Description
max_concurrent_trials	Optional[int] The maximum number of concurrent trials for the Sweep Job.
max_total_trials	Optional[int] The maximum number of total trials for the Sweep Job.
timeout	Optional[int] The maximum run duration, in seconds, after which the job will be cancelled.
trial_timeout	Optional[int] The timeout value, in seconds, for each Sweep Job trial.

Examples

Assigning limits to a SweepJob

   from azure.ai.ml.entities import CommandJob
   from azure.ai.ml.sweep import BayesianSamplingAlgorithm, Objective, SweepJob, SweepJobLimits

   command_job = CommandJob(
       inputs=dict(kernel="linear", penalty=1.0),
       compute=cpu_cluster,
       environment=f"{job_env.name}:{job_env.version}",
       code="./scripts",
       command="python scripts/train.py --kernel $kernel --penalty $penalty",
       experiment_name="sklearn-iris-flowers",
   )

   sweep = SweepJob(
       sampling_algorithm=BayesianSamplingAlgorithm(),
       trial=command_job,
       search_space={"ss": Choice(type="choice", values=[{"space1": True}, {"space2": True}])},
       inputs={"input1": {"file": "top_level.csv", "mode": "ro_mount"}},
       compute="top_level",
       limits=SweepJobLimits(trial_timeout=600),
       objective=Objective(goal="maximize", primary_metric="accuracy"),
   )

Attributes

timeout

The maximum run duration, in seconds, after which the job will be cancelled.

Returns

Type	Description
int	The maximum run duration, in seconds, after which the job will be cancelled.

trial_timeout

The timeout value, in seconds, for each Sweep Job trial.

Returns

Type	Description
int	The timeout value, in seconds, for each Sweep Job trial.