CleanRoomsML / Client / get_collaboration_ml_input_channel

get_collaboration_ml_input_channel¶

CleanRoomsML.Client.get_collaboration_ml_input_channel(**kwargs)¶

Returns information about a specific ML input channel in a collaboration.

Request Syntax

response = client.get_collaboration_ml_input_channel(
    mlInputChannelArn='string',
    collaborationIdentifier='string'
)

Parameters:

mlInputChannelArn (string) –
[REQUIRED]

The Amazon Resource Name (ARN) of the ML input channel that you want to get.
collaborationIdentifier (string) –
[REQUIRED]

The collaboration ID of the collaboration that contains the ML input channel that you want to get.

Return type:

dict

Returns:

Response Syntax

{
    'membershipIdentifier': 'string',
    'collaborationIdentifier': 'string',
    'mlInputChannelArn': 'string',
    'name': 'string',
    'configuredModelAlgorithmAssociations': [
        'string',
    ],
    'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE',
    'statusDetails': {
        'statusCode': 'string',
        'message': 'string'
    },
    'retentionInDays': 123,
    'numberOfRecords': 123,
    'privacyBudgets': {
        'accessBudgets': [
            {
                'resourceArn': 'string',
                'details': [
                    {
                        'startTime': datetime(2015, 1, 1),
                        'endTime': datetime(2015, 1, 1),
                        'remainingBudget': 123,
                        'budget': 123,
                        'budgetType': 'CALENDAR_DAY'|'CALENDAR_MONTH'|'CALENDAR_WEEK'|'LIFETIME',
                        'autoRefresh': 'ENABLED'|'DISABLED'
                    },
                ],
                'aggregateRemainingBudget': 123
            },
        ]
    },
    'description': 'string',
    'syntheticDataConfiguration': {
        'syntheticDataParameters': {
            'epsilon': 123.0,
            'maxMembershipInferenceAttackScore': 123.0,
            'columnClassification': {
                'columnMapping': [
                    {
                        'columnName': 'string',
                        'columnType': 'CATEGORICAL'|'NUMERICAL',
                        'isPredictiveValue': True|False
                    },
                ]
            }
        },
        'syntheticDataEvaluationScores': {
            'dataPrivacyScores': {
                'membershipInferenceAttackScores': [
                    {
                        'attackVersion': 'DISTANCE_TO_CLOSEST_RECORD_V1',
                        'score': 123.0
                    },
                ]
            }
        }
    },
    'createTime': datetime(2015, 1, 1),
    'updateTime': datetime(2015, 1, 1),
    'creatorAccountId': 'string'
}

Response Structure

(dict) –
- membershipIdentifier (string) –
  
  The membership ID of the membership that contains the ML input channel.
- collaborationIdentifier (string) –
  
  The collaboration ID of the collaboration that contains the ML input channel.
- mlInputChannelArn (string) –
  
  The Amazon Resource Name (ARN) of the ML input channel.
- name (string) –
  
  The name of the ML input channel.
- configuredModelAlgorithmAssociations (list) –
  
  The configured model algorithm associations that were used to create the ML input channel.
  - (string) –
- status (string) –
  
  The status of the ML input channel.
- statusDetails (dict) –
  
  Details about the status of a resource.
  - statusCode (string) –
    
    The status code that was returned. The status code is intended for programmatic error handling. Clean Rooms ML will not change the status code for existing error conditions.
  - message (string) –
    
    The error message that was returned. The message is intended for human consumption and can change at any time. Use the statusCode for programmatic error handling.
- retentionInDays (integer) –
  
  The number of days to retain the data for the ML input channel.
- numberOfRecords (integer) –
  
  The number of records in the ML input channel.
- privacyBudgets (dict) –
  
  Returns the privacy budgets that control access to this Clean Rooms ML input channel. Use these budgets to monitor and limit resource consumption over specified time periods.
  Note
  This is a Tagged Union structure. Only one of the following top level keys will be set: accessBudgets. If a client receives an unknown member it will set SDK_UNKNOWN_MEMBER as the top level key, which maps to the name or tag of the unknown member. The structure of SDK_UNKNOWN_MEMBER is as follows:
  'SDK_UNKNOWN_MEMBER': {'name': 'UnknownMemberName'}
  - accessBudgets (list) –
    
    A list of access budgets that apply to resources associated with this Clean Rooms ML input channel.
    - (dict) –
      
      An access budget that defines consumption limits for a specific resource within defined time periods.
      - resourceArn (string) –
        
        The Amazon Resource Name (ARN) of the resource that this access budget applies to.
      - details (list) –
        
        A list of budget details for this resource. Contains active budget periods that apply to the resource.
        
        (dict) –
        
        The detailed information for a specific budget period, including time boundaries and budget amounts.
        
        startTime (datetime) –
        
        The start time of this budget period.
        
        endTime (datetime) –
        
        The end time of this budget period. If not specified, the budget period continues indefinitely.
        
        remainingBudget (integer) –
        
        The amount of budget remaining in this period.
        
        budget (integer) –
        
        The total budget amount allocated for this period.
        
        budgetType (string) –
        
        The type of budget period. Calendar-based types reset automatically at regular intervals, while LIFETIME budgets never reset.
        
        autoRefresh (string) –
        
        Specifies whether this budget automatically refreshes when the current period ends.
      - aggregateRemainingBudget (integer) –
        
        The total remaining budget across all active budget periods for this resource.
- description (string) –
  
  The description of the ML input channel.
- syntheticDataConfiguration (dict) –
  
  The synthetic data configuration for this ML input channel, including parameters for generating privacy-preserving synthetic data and evaluation scores for measuring the privacy of the generated data.
  - syntheticDataParameters (dict) –
    
    The parameters that control how synthetic data is generated, including privacy settings, column classifications, and other configuration options that affect the data synthesis process.
    - epsilon (float) –
      
      The epsilon value for differential privacy, which controls the privacy-utility tradeoff in synthetic data generation. Lower values provide stronger privacy guarantees but may reduce data utility.
    - maxMembershipInferenceAttackScore (float) –
      
      The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
    - columnClassification (dict) –
      
      Classification details for data columns that specify how each column should be treated during synthetic data generation.
      - columnMapping (list) –
        
        A mapping that defines the classification of data columns for synthetic data generation and specifies how each column should be handled during the privacy-preserving data synthesis process.
        
        (dict) –
        
        Properties that define how a specific data column should be handled during synthetic data generation, including its name, type, and role in predictive modeling.
        
        columnName (string) –
        
        The name of the data column as it appears in the dataset.
        
        columnType (string) –
        
        The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.
        
        isPredictiveValue (boolean) –
        
        Indicates if this column contains predictive values that should be treated as target variables in machine learning models. This affects how the synthetic data generation preserves statistical relationships.
  - syntheticDataEvaluationScores (dict) –
    
    Evaluation scores that assess the quality and privacy characteristics of the generated synthetic data, providing metrics on data utility and privacy preservation.
    - dataPrivacyScores (dict) –
      
      Privacy-specific evaluation scores that measure how well the synthetic data protects individual privacy, including assessments of potential privacy risks such as membership inference attacks.
      - membershipInferenceAttackScores (list) –
        
        Scores that evaluate the vulnerability of the synthetic data to membership inference attacks, which attempt to determine whether a specific individual was a member of the original dataset.
        
        (dict) –
        
        A score that measures the vulnerability of synthetic data to membership inference attacks and provides both the numerical score and the version of the attack methodology used for evaluation.
        
        attackVersion (string) –
        
        The version of the membership inference attack, which consists of the attack type and its version number, used to generate this privacy score.
        
        score (float) –
        
        The numerical score representing the vulnerability to membership inference attacks.
- createTime (datetime) –
  
  The time at which the ML input channel was created.
- updateTime (datetime) –
  
  The most recent time at which the ML input channel was updated.
- creatorAccountId (string) –
  
  The account ID of the member who created the ML input channel.

get_collaboration_ml_input_channel¶

Request Syntax

Response Syntax

Response Structure

Note

Exceptions