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get_collaboration_configured_model_algorithm_association

get_collaboration_configured_model_algorithm_association(
    configured_model_algorithm_association_arn: ConfiguredModelAlgorithmAssociationArn,
    collaboration_identifier: UUID,
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
) -> GetCollaborationConfiguredModelAlgorithmAssociationResponse

Returns information about the configured model algorithm association in a collaboration.

Parameters:

  • configured_model_algorithm_association_arn (ConfiguredModelAlgorithmAssociationArn) –

    The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

  • collaboration_identifier (UUID) –

    The collaboration ID for the collaboration that contains the configured model algorithm association that you want to return information about.

Raises:

Source code in docs_src/capo_cleanroomsml/_services/clean_rooms_ml.py
def get_collaboration_configured_model_algorithm_association(
    self,
    configured_model_algorithm_association_arn: "capo_cleanroomsml.types.configured_model_algorithm_association_arn.ConfiguredModelAlgorithmAssociationArn",
    collaboration_identifier: "capo_cleanroomsml.types.uuid.UUID",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
) -> "capo_cleanroomsml.types.get_collaboration_configured_model_algorithm_association_response.GetCollaborationConfiguredModelAlgorithmAssociationResponse":
    """<p>Returns information about the configured model algorithm association in a collaboration.</p>

    Args:
        configured_model_algorithm_association_arn: <p>The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.</p>
        collaboration_identifier: <p>The collaboration ID for the collaboration that contains the configured model algorithm association that you want to return information about.</p>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_cleanroomsml.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource you are requesting does not exist.</p>
        capo_cleanroomsml.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_cleanroomsml.errors.validation_exception.ValidationException: <p>The request parameters for this request are incorrect.</p>
        capo_cleanroomsml.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_cleanroomsml.types.get_collaboration_configured_model_algorithm_association_request.GetCollaborationConfiguredModelAlgorithmAssociationRequest]",
    ) -> OperationResponse[
        "capo_cleanroomsml.types.get_collaboration_configured_model_algorithm_association_response.GetCollaborationConfiguredModelAlgorithmAssociationResponse"
    ]:
        import capo_cleanroomsml._operations.aws_stark_control_service.get_collaboration_configured_model_algorithm_association

        output, http_response = (
            capo_cleanroomsml._operations.aws_stark_control_service.get_collaboration_configured_model_algorithm_association.get_collaboration_configured_model_algorithm_association(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("GetCollaborationConfiguredModelAlgorithmAssociation"),
    )
    input_: capo_cleanroomsml.types.get_collaboration_configured_model_algorithm_association_request.GetCollaborationConfiguredModelAlgorithmAssociationRequest = {
        "configured_model_algorithm_association_arn": configured_model_algorithm_association_arn,
        "collaboration_identifier": collaboration_identifier,
    }

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