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RandomSamplingAlgorithm Class

  • Reference

Random Sampling Algorithm.

Inheritance
azure.ai.ml.entities._job.sweep.sampling_algorithm.SamplingAlgorithm
RandomSamplingAlgorithm

Constructor

RandomSamplingAlgorithm(*, rule: str | None = None, seed: int | None = None, logbase: float | str | None = None)

Keyword-Only Parameters

Name Description
rule

The specific type of random algorithm. Accepted values are: "random" and "sobol".
seed
int

The seed for random number generation.
logbase
Union[float, str]

A positive number or the number "e" in string format to be used as the base for log based random sampling.

Examples

Assigning a random sampling algorithm for a SweepJob


   from azure.ai.ml.entities import CommandJob
   from azure.ai.ml.sweep import RandomSamplingAlgorithm, 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=RandomSamplingAlgorithm(seed=999, rule="sobol", logbase="e"),
       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),
   )