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SweepJobLimits Class
Limits for Sweep Jobs.
- Inheritance
-
azure.ai.ml.entities._job.job_limits.JobLimitsSweepJobLimits
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
|
The maximum number of concurrent trials for the Sweep Job. |
max_total_trials
|
The maximum number of total trials for the Sweep Job. |
timeout
|
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. |
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 |
---|---|
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 |
---|---|
The timeout value, in seconds, for each Sweep Job trial. |