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StopInferenceExperimentRequest

Source code in docs_src/capo_sagemaker/types/stop_inference_experiment_request.py 
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class StopInferenceExperimentRequest(TypedDict, closed=True):
    name: NotRequired[
        "capo_sagemaker.types.inference_experiment_name.InferenceExperimentName"
    ]
    """<p>The name of the inference experiment to stop.</p>"""
    model_variant_actions: NotRequired[
        "capo_sagemaker.types.model_variant_action_map.ModelVariantActionMap"
    ]
    """<p> Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following: </p> <ul> <li> <p> <code>Promote</code> - Promote the shadow variant to a production variant</p> </li> <li> <p> <code>Remove</code> - Delete the variant</p> </li> <li> <p> <code>Retain</code> - Keep the variant as it is</p> </li> </ul>"""
    desired_model_variants: NotRequired[
        "capo_sagemaker.types.model_variant_config_list.ModelVariantConfigList"
    ]
    """<p> An array of <code>ModelVariantConfig</code> objects. There is one for each variant that you want to deploy after the inference experiment stops. Each <code>ModelVariantConfig</code> describes the infrastructure configuration for deploying the corresponding variant. </p>"""
    desired_state: NotRequired[
        "capo_sagemaker.types.inference_experiment_stop_desired_state.InferenceExperimentStopDesiredState"
    ]
    """<p> The desired state of the experiment after stopping. The possible states are the following: </p> <ul> <li> <p> <code>Completed</code>: The experiment completed successfully</p> </li> <li> <p> <code>Cancelled</code>: The experiment was canceled</p> </li> </ul>"""
    reason: NotRequired[
        "capo_sagemaker.types.inference_experiment_status_reason.InferenceExperimentStatusReason"
    ]
    """<p>The reason for stopping the experiment.</p>"""

desired_model_variants instance-attribute 

desired_model_variants: NotRequired[ModelVariantConfigList]

An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.

desired_state instance-attribute 

desired_state: NotRequired[InferenceExperimentStopDesiredState]

The desired state of the experiment after stopping. The possible states are the following:

  • Completed: The experiment completed successfully

  • Cancelled: The experiment was canceled

model_variant_actions instance-attribute 

model_variant_actions: NotRequired[ModelVariantActionMap]

Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:

  • Promote - Promote the shadow variant to a production variant

  • Remove - Delete the variant

  • Retain - Keep the variant as it is

name instance-attribute 

name: NotRequired[InferenceExperimentName]

The name of the inference experiment to stop.

reason instance-attribute 

reason: NotRequired[InferenceExperimentStatusReason]

The reason for stopping the experiment.