CleanRoomsML / Client / get_ml_input_channel

get_ml_input_channel

CleanRoomsML.Client.get_ml_input_channel(**kwargs)

Returns information about an ML input channel.

See also: AWS API Documentation

Request Syntax

response = client.get_ml_input_channel(
    mlInputChannelArn='string',
    membershipIdentifier='string'
)
Parameters:

  • mlInputChannelArn (string) –

    [REQUIRED]

    The Amazon Resource Name (ARN) of the ML input channel that you want to get.

  • membershipIdentifier (string) –

    [REQUIRED]

    The membership ID of the membership 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),
    'inputChannel': {
        'dataSource': {
            'protectedQueryInputParameters': {
                'sqlParameters': {
                    'queryString': 'string',
                    'analysisTemplateArn': 'string',
                    'parameters': {
                        'string': 'string'
                    }
                },
                'computeConfiguration': {
                    'worker': {
                        'type': 'CR.1X'|'CR.4X',
                        'number': 123
                    }
                },
                'resultFormat': 'CSV'|'PARQUET'
            }
        },
        'roleArn': 'string'
    },
    'protectedQueryIdentifier': 'string',
    'numberOfFiles': 123.0,
    'sizeInGb': 123.0,
    'kmsKeyArn': 'string',
    'tags': {
        'string': '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 keep the data in 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.

    • inputChannel (dict) –

      The input channel that was used to create the ML input channel.

      • dataSource (dict) –

        The data source that is used to create the ML input channel.

        Note

        This is a Tagged Union structure. Only one of the following top level keys will be set: protectedQueryInputParameters. 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'}

        • protectedQueryInputParameters (dict) –

          Provides information necessary to perform the protected query.

          • sqlParameters (dict) –

            The parameters for the SQL type Protected Query.

            • queryString (string) –

              The query string to be submitted.

            • analysisTemplateArn (string) –

              The Amazon Resource Name (ARN) associated with the analysis template within a collaboration.

            • parameters (dict) –

              The protected query SQL parameters.

              • (string) –

                • (string) –

          • computeConfiguration (dict) –

            Provides configuration information for the workers that will perform the protected query.

            Note

            This is a Tagged Union structure. Only one of the following top level keys will be set: worker. 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'}

            • worker (dict) –

              The worker instances that will perform the compute work.

              • type (string) –

                The instance type of the compute workers that are used.

              • number (integer) –

                The number of compute workers that are used.

          • resultFormat (string) –

            The format in which the query results should be returned. If not specified, defaults to CSV.

      • roleArn (string) –

        The Amazon Resource Name (ARN) of the role used to run the query specified in the dataSource field of the input channel.

        Passing a role across AWS accounts is not allowed. If you pass a role that isn’t in your account, you get an AccessDeniedException error.

    • protectedQueryIdentifier (string) –

      The ID of the protected query that was used to create the ML input channel.

    • numberOfFiles (float) –

      The number of files in the ML input channel.

    • sizeInGb (float) –

      The size, in GB, of the ML input channel.

    • kmsKeyArn (string) –

      The Amazon Resource Name (ARN) of the KMS key that was used to create the ML input channel.

    • tags (dict) –

      The optional metadata that you applied 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) –

Exceptions