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Choice Class

Choice distribution configuration.

Constructor

Choice(values: List[float | str | dict] | None = None, **kwargs: Any)

Parameters

Name Description
values
list[Union[float, str, dict]]

List of values to choose from.

Default value: None

Examples

Using Choice distribution to set values for a hyperparameter sweep


   from azure.ai.ml import command

   job = command(
       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",
   )

   from azure.ai.ml.sweep import Choice, LogUniform

   # we can reuse an existing Command Job as a function that we can apply inputs to for the sweep configurations
   job_for_sweep = job(
       kernel=LogUniform(min_value=-6, max_value=-1),
       penalty=Choice([0.9, 0.18, 0.36, 0.72]),
   )