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delete_evaluation 

delete_evaluation(
    evaluation_id: EntityId,
    *,
    config_overrides: Optional[MachineLearningClientConfig] = None,
) -> DeleteEvaluationOutput

Assigns the DELETED status to an Evaluation, rendering it unusable.

After invoking the DeleteEvaluation operation, you can use the GetEvaluation operation to verify that the status of the Evaluation changed to DELETED.

Caution: The results of the DeleteEvaluation operation are irreversible.

Parameters:

  • evaluation_id (EntityId) –

    A user-supplied ID that uniquely identifies the Evaluation to delete.

Raises:

Source code in docs_src/capo_machine_learning/_services/machine_learning.py 
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def delete_evaluation(
    self,
    evaluation_id: "capo_machine_learning.types.entity_id.EntityId",
    *,
    config_overrides: Optional[MachineLearningClientConfig] = None,
) -> "capo_machine_learning.types.delete_evaluation_output.DeleteEvaluationOutput":
    """<p>Assigns the <code>DELETED</code> status to an <code>Evaluation</code>, rendering it unusable.</p> <p>After invoking the <code>DeleteEvaluation</code> operation, you can use the <code>GetEvaluation</code> operation to verify that the status of the <code>Evaluation</code> changed to <code>DELETED</code>.</p> <p> <b>Caution:</b> The results of the <code>DeleteEvaluation</code> operation are irreversible.</p>

    Args:
        evaluation_id: <p>A user-supplied ID that uniquely identifies the <code>Evaluation</code> to delete.</p>

    Raises:
        capo_machine_learning.errors.internal_server_exception.InternalServerException: <p>An error on the server occurred when trying to process a request.</p>
        capo_machine_learning.errors.invalid_input_exception.InvalidInputException: <p>An error on the client occurred. Typically, the cause is an invalid input value.</p>
        capo_machine_learning.errors.resource_not_found_exception.ResourceNotFoundException: <p>A specified resource cannot be located.</p>
        capo_machine_learning.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_machine_learning.types.delete_evaluation_input.DeleteEvaluationInput]",
    ) -> OperationResponse[
        "capo_machine_learning.types.delete_evaluation_output.DeleteEvaluationOutput"
    ]:
        import capo_machine_learning._operations.amazon_ml_20141212.delete_evaluation

        output, http_response = (
            capo_machine_learning._operations.amazon_ml_20141212.delete_evaluation.delete_evaluation(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteEvaluation")
    )
    input_: capo_machine_learning.types.delete_evaluation_input.DeleteEvaluationInput = {
        "evaluation_id": evaluation_id
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output