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SweepJobLimits Class

  • Reference

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.