:doc:`CleanRoomsML <../../cleanroomsml>` / Client / create_configured_model_algorithm_association

*********************************************
create_configured_model_algorithm_association
*********************************************



.. py:method:: CleanRoomsML.Client.create_configured_model_algorithm_association(**kwargs)

  

  Associates a configured model algorithm to a collaboration for use by any member of the collaboration.

  

  See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/cleanroomsml-2023-09-06/CreateConfiguredModelAlgorithmAssociation>`_  


  **Request Syntax**
  ::

    response = client.create_configured_model_algorithm_association(
        membershipIdentifier='string',
        configuredModelAlgorithmArn='string',
        name='string',
        description='string',
        privacyConfiguration={
            'policies': {
                'trainedModels': {
                    'containerLogs': [
                        {
                            'allowedAccountIds': [
                                'string',
                            ],
                            'filterPattern': 'string',
                            'logType': 'ALL'|'ERROR_SUMMARY',
                            'logRedactionConfiguration': {
                                'entitiesToRedact': [
                                    'ALL_PERSONALLY_IDENTIFIABLE_INFORMATION'|'NUMBERS'|'CUSTOM',
                                ],
                                'customEntityConfig': {
                                    'customDataIdentifiers': [
                                        'string',
                                    ]
                                }
                            }
                        },
                    ],
                    'containerMetrics': {
                        'noiseLevel': 'HIGH'|'MEDIUM'|'LOW'|'NONE'
                    },
                    'maxArtifactSize': {
                        'unit': 'GB',
                        'value': 123.0
                    }
                },
                'trainedModelExports': {
                    'maxSize': {
                        'unit': 'GB',
                        'value': 123.0
                    },
                    'filesToExport': [
                        'MODEL'|'OUTPUT',
                    ]
                },
                'trainedModelInferenceJobs': {
                    'containerLogs': [
                        {
                            'allowedAccountIds': [
                                'string',
                            ],
                            'filterPattern': 'string',
                            'logType': 'ALL'|'ERROR_SUMMARY',
                            'logRedactionConfiguration': {
                                'entitiesToRedact': [
                                    'ALL_PERSONALLY_IDENTIFIABLE_INFORMATION'|'NUMBERS'|'CUSTOM',
                                ],
                                'customEntityConfig': {
                                    'customDataIdentifiers': [
                                        'string',
                                    ]
                                }
                            }
                        },
                    ],
                    'maxOutputSize': {
                        'unit': 'GB',
                        'value': 123.0
                    }
                }
            }
        },
        tags={
            'string': 'string'
        }
    )
    
  :type membershipIdentifier: string
  :param membershipIdentifier: **[REQUIRED]** 

    The membership ID of the member who is associating this configured model algorithm.

    

  
  :type configuredModelAlgorithmArn: string
  :param configuredModelAlgorithmArn: **[REQUIRED]** 

    The Amazon Resource Name (ARN) of the configured model algorithm that you want to associate.

    

  
  :type name: string
  :param name: **[REQUIRED]** 

    The name of the configured model algorithm association.

    

  
  :type description: string
  :param description: 

    The description of the configured model algorithm association.

    

  
  :type privacyConfiguration: dict
  :param privacyConfiguration: 

    Specifies the privacy configuration information for the configured model algorithm association. This information includes the maximum data size that can be exported.

    

  
    - **policies** *(dict) --* **[REQUIRED]** 

      The privacy configuration policies for a configured model algorithm association.

      

    
      - **trainedModels** *(dict) --* 

        Specifies who will receive the trained models.

        

      
        - **containerLogs** *(list) --* 

          The container for the logs of the trained model.

          

        
          - *(dict) --* 

            Provides the information necessary for a user to access the logs.

            

          
            - **allowedAccountIds** *(list) --* **[REQUIRED]** 

              A list of account IDs that are allowed to access the logs.

              

            
              - *(string) --* 

              
          
            - **filterPattern** *(string) --* 

              A regular expression pattern that is used to parse the logs and return information that matches the pattern.

              

            
            - **logType** *(string) --* 

              Specifies the type of log this policy applies to. The currently supported policies are ALL or ERROR_SUMMARY.

              

            
            - **logRedactionConfiguration** *(dict) --* 

              Specifies the log redaction configuration for this policy.

              

            
              - **entitiesToRedact** *(list) --* **[REQUIRED]** 

                Specifies the entities to be redacted from logs. Entities to redact are "ALL_PERSONALLY_IDENTIFIABLE_INFORMATION", "NUMBERS","CUSTOM". If CUSTOM is supplied or configured, custom patterns (customDataIdentifiers) should be provided, and the patterns will be redacted in logs or error messages.

                

              
                - *(string) --* 

                
            
              - **customEntityConfig** *(dict) --* 

                Specifies the configuration for custom entities in the context of log redaction.

                

              
                - **customDataIdentifiers** *(list) --* **[REQUIRED]** 

                  Defines data identifiers for the custom entity configuration. Provide this only if CUSTOM redaction is configured.

                  

                
                  - *(string) --* 

                  
              
              
            
          
      
        - **containerMetrics** *(dict) --* 

          The container for the metrics of the trained model.

          

        
          - **noiseLevel** *(string) --* **[REQUIRED]** 

            The noise level for the generated metrics.

            

          
        
        - **maxArtifactSize** *(dict) --* 

          The maximum size limit for trained model artifacts as defined in the configuration policy. This setting helps enforce consistent size limits across trained models in the collaboration.

          

        
          - **unit** *(string) --* **[REQUIRED]** 

            The unit of measurement for the maximum artifact size. Valid values include common storage units such as bytes, kilobytes, megabytes, gigabytes, and terabytes.

            

          
          - **value** *(float) --* **[REQUIRED]** 

            The numerical value for the maximum artifact size limit. This value is interpreted according to the specified unit.

            

          
        
      
      - **trainedModelExports** *(dict) --* 

        Specifies who will receive the trained model export.

        

      
        - **maxSize** *(dict) --* **[REQUIRED]** 

          The maximum size of the data that can be exported.

          

        
          - **unit** *(string) --* **[REQUIRED]** 

            The unit of measurement for the data size.

            

          
          - **value** *(float) --* **[REQUIRED]** 

            The maximum size of the dataset to export.

            

          
        
        - **filesToExport** *(list) --* **[REQUIRED]** 

          The files that are exported during the trained model export job.

          

        
          - *(string) --* 

          
      
      
      - **trainedModelInferenceJobs** *(dict) --* 

        Specifies who will receive the trained model inference jobs.

        

      
        - **containerLogs** *(list) --* 

          The logs container for the trained model inference job.

          

        
          - *(dict) --* 

            Provides the information necessary for a user to access the logs.

            

          
            - **allowedAccountIds** *(list) --* **[REQUIRED]** 

              A list of account IDs that are allowed to access the logs.

              

            
              - *(string) --* 

              
          
            - **filterPattern** *(string) --* 

              A regular expression pattern that is used to parse the logs and return information that matches the pattern.

              

            
            - **logType** *(string) --* 

              Specifies the type of log this policy applies to. The currently supported policies are ALL or ERROR_SUMMARY.

              

            
            - **logRedactionConfiguration** *(dict) --* 

              Specifies the log redaction configuration for this policy.

              

            
              - **entitiesToRedact** *(list) --* **[REQUIRED]** 

                Specifies the entities to be redacted from logs. Entities to redact are "ALL_PERSONALLY_IDENTIFIABLE_INFORMATION", "NUMBERS","CUSTOM". If CUSTOM is supplied or configured, custom patterns (customDataIdentifiers) should be provided, and the patterns will be redacted in logs or error messages.

                

              
                - *(string) --* 

                
            
              - **customEntityConfig** *(dict) --* 

                Specifies the configuration for custom entities in the context of log redaction.

                

              
                - **customDataIdentifiers** *(list) --* **[REQUIRED]** 

                  Defines data identifiers for the custom entity configuration. Provide this only if CUSTOM redaction is configured.

                  

                
                  - *(string) --* 

                  
              
              
            
          
      
        - **maxOutputSize** *(dict) --* 

          The maximum allowed size of the output of the trained model inference job.

          

        
          - **unit** *(string) --* **[REQUIRED]** 

            The measurement unit to use.

            

          
          - **value** *(float) --* **[REQUIRED]** 

            The maximum output size value.

            

          
        
      
    
  
  :type tags: dict
  :param tags: 

    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.

     

    The following basic restrictions apply to tags:

     

    
    * Maximum number of tags per resource - 50.
     
    * For each resource, each tag key must be unique, and each tag key can have only one value.
     
    * Maximum key length - 128 Unicode characters in UTF-8.
     
    * Maximum value length - 256 Unicode characters in UTF-8.
     
    * 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: + - = . _ : / @.
     
    * Tag keys and values are case sensitive.
     
    * 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.
    

    

  
    - *(string) --* 

    
      - *(string) --* 

      


  
  :rtype: dict
  :returns: 
    
    **Response Syntax**

    
    ::

      {
          'configuredModelAlgorithmAssociationArn': 'string'
      }
      
    **Response Structure**

    

    - *(dict) --* 
      

      - **configuredModelAlgorithmAssociationArn** *(string) --* 

        The Amazon Resource Name (ARN) of the configured model algorithm association.

        
  
  **Exceptions**
  
  *   :py:class:`CleanRoomsML.Client.exceptions.ConflictException`

  
  *   :py:class:`CleanRoomsML.Client.exceptions.ValidationException`

  
  *   :py:class:`CleanRoomsML.Client.exceptions.AccessDeniedException`

  
  *   :py:class:`CleanRoomsML.Client.exceptions.ResourceNotFoundException`

  
  *   :py:class:`CleanRoomsML.Client.exceptions.ThrottlingException`

  
  *   :py:class:`CleanRoomsML.Client.exceptions.ServiceQuotaExceededException`

  