create_configured_model_algorithm_association ¶

def create_configured_model_algorithm_association(
    self,
    membership_identifier: "capo_cleanroomsml.types.uuid.UUID",
    configured_model_algorithm_arn: "capo_cleanroomsml.types.configured_model_algorithm_arn.ConfiguredModelAlgorithmArn",
    name: "capo_cleanroomsml.types.name_string.NameString",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
    description: Optional[
        "capo_cleanroomsml.types.resource_description.ResourceDescription"
    ] = None,
    privacy_configuration: Optional[
        "capo_cleanroomsml.types.privacy_configuration.PrivacyConfiguration"
    ] = None,
    tags: Optional["capo_cleanroomsml.types.tag_map.TagMap"] = None,
) -> "capo_cleanroomsml.types.create_configured_model_algorithm_association_response.CreateConfiguredModelAlgorithmAssociationResponse":
    """<p>Associates a configured model algorithm to a collaboration for use by any member of the collaboration.</p>

    Args:
        membership_identifier: <p>The membership ID of the member who is associating this configured model algorithm.</p>
        configured_model_algorithm_arn: <p>The Amazon Resource Name (ARN) of the configured model algorithm that you want to associate.</p>
        name: <p>The name of the configured model algorithm association.</p>
        description: <p>The description of the configured model algorithm association.</p>
        privacy_configuration: <p>Specifies the privacy configuration information for the configured model algorithm association. This information includes the maximum data size that can be exported.</p>
        tags: <p>The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.</p> <p>The following basic restrictions apply to tags:</p> <ul> <li> <p>Maximum number of tags per resource - 50.</p> </li> <li> <p>For each resource, each tag key must be unique, and each tag key can have only one value.</p> </li> <li> <p>Maximum key length - 128 Unicode characters in UTF-8.</p> </li> <li> <p>Maximum value length - 256 Unicode characters in UTF-8.</p> </li> <li> <p>If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.</p> </li> <li> <p>Tag keys and values are case sensitive.</p> </li> <li> <p>Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.</p> </li> </ul>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_cleanroomsml.errors.conflict_exception.ConflictException: <p>You can't complete this action because another resource depends on this resource.</p>
        capo_cleanroomsml.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource you are requesting does not exist.</p>
        capo_cleanroomsml.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have exceeded your service quota.</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.create_configured_model_algorithm_association_request.CreateConfiguredModelAlgorithmAssociationRequest]",
    ) -> OperationResponse[
        "capo_cleanroomsml.types.create_configured_model_algorithm_association_response.CreateConfiguredModelAlgorithmAssociationResponse"
    ]:
        import capo_cleanroomsml._operations.aws_stark_control_service.create_configured_model_algorithm_association

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

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("CreateConfiguredModelAlgorithmAssociation"),
    )
    input_: capo_cleanroomsml.types.create_configured_model_algorithm_association_request.CreateConfiguredModelAlgorithmAssociationRequest = {
        "membership_identifier": membership_identifier,
        "configured_model_algorithm_arn": configured_model_algorithm_arn,
        "name": name,
    }
    if description is not None:
        input_["description"] = description
    if privacy_configuration is not None:
        input_["privacy_configuration"] = privacy_configuration
    if tags is not None:
        input_["tags"] = tags

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