AWS CLI Command Reference

[ aws . cleanroomsml ]

get-collaboration-ml-input-channel

Description

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

See also: AWS API Documentation

Synopsis

  get-collaboration-ml-input-channel
--ml-input-channel-arn <value>
--collaboration-identifier <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--ml-input-channel-arn (string) [required]

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

Constraints:

  • min: 20
  • max: 2048
  • pattern: arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/ml-input-channel/[-a-zA-Z0-9_/.]+

--collaboration-identifier (string) [required]

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

Constraints:

  • min: 36
  • max: 36
  • pattern: [0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

  • json
  • text
  • table
  • yaml
  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on
  • off
  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64
  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Output

membershipIdentifier -> (string)

The membership ID of the membership that contains the ML input channel.

Constraints:

  • min: 36
  • max: 36
  • pattern: [0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}

collaborationIdentifier -> (string)

The collaboration ID of the collaboration that contains the ML input channel.

Constraints:

  • min: 36
  • max: 36
  • pattern: [0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}

mlInputChannelArn -> (string)

The Amazon Resource Name (ARN) of the ML input channel.

Constraints:

  • min: 20
  • max: 2048
  • pattern: arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/ml-input-channel/[-a-zA-Z0-9_/.]+

name -> (string)

The name of the ML input channel.

Constraints:

  • min: 1
  • max: 63
  • pattern: (?!\s*$)[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDBFF-\uDC00\uDFFF\t]*

configuredModelAlgorithmAssociations -> (list)

The configured model algorithm associations that were used to create the ML input channel.

Constraints:

  • min: 1
  • max: 1

(string)

Constraints:

  • min: 20
  • max: 2048
  • pattern: arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/configured-model-algorithm-association/[-a-zA-Z0-9_/.]+

status -> (string)

The status of the ML input channel.

Possible values:

  • CREATE_PENDING
  • CREATE_IN_PROGRESS
  • CREATE_FAILED
  • ACTIVE
  • DELETE_PENDING
  • DELETE_IN_PROGRESS
  • DELETE_FAILED
  • INACTIVE

statusDetails -> (structure)

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.

Constraints:

  • min: 1
  • max: 30

numberOfRecords -> (long)

The number of records in the ML input channel.

Constraints:

  • min: 0
  • max: 100000000000

privacyBudgets -> (tagged union structure)

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 can be set: accessBudgets.

accessBudgets -> (list)

A list of access budgets that apply to resources associated with this Clean Rooms ML input channel.

Constraints:

  • min: 1
  • max: 100

(structure)

An access budget that defines consumption limits for a specific resource within defined time periods.

resourceArn -> (string) [required]

The Amazon Resource Name (ARN) of the resource that this access budget applies to.

Constraints:

  • min: 0
  • max: 200
  • pattern: arn:aws:[\w]+:[\w]{2}-[\w]{4,9}-[\d]:[\d]{12}:membership/[\d\w-]+/configuredtableassociation/[\d\w-]+

details -> (list) [required]

A list of budget details for this resource. Contains active budget periods that apply to the resource.

Constraints:

  • min: 1
  • max: 2

(structure)

The detailed information for a specific budget period, including time boundaries and budget amounts.

startTime -> (timestamp) [required]

The start time of this budget period.

endTime -> (timestamp)

The end time of this budget period. If not specified, the budget period continues indefinitely.

remainingBudget -> (integer) [required]

The amount of budget remaining in this period.

Constraints:

  • min: 0

budget -> (integer) [required]

The total budget amount allocated for this period.

Constraints:

  • min: 0

budgetType -> (string) [required]

The type of budget period. Calendar-based types reset automatically at regular intervals, while LIFETIME budgets never reset.

Possible values:

  • CALENDAR_DAY
  • CALENDAR_MONTH
  • CALENDAR_WEEK
  • LIFETIME

autoRefresh -> (string)

Specifies whether this budget automatically refreshes when the current period ends.

Possible values:

  • ENABLED
  • DISABLED

aggregateRemainingBudget -> (integer) [required]

The total remaining budget across all active budget periods for this resource.

Constraints:

  • min: 0

description -> (string)

The description of the ML input channel.

Constraints:

  • min: 0
  • max: 255
  • pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDBFF-\uDC00\uDFFF\t\r\n]*

syntheticDataConfiguration -> (structure)

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 -> (structure) [required]

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 -> (double) [required]

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.

Constraints:

  • min: 0.0001
  • max: 10

maxMembershipInferenceAttackScore -> (double) [required]

The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.

Constraints:

  • min: 0.5
  • max: 1

columnClassification -> (structure) [required]

Classification details for data columns that specify how each column should be treated during synthetic data generation.

columnMapping -> (list) [required]

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.

Constraints:

  • min: 5

(structure)

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) [required]

The name of the data column as it appears in the dataset.

Constraints:

  • min: 0
  • max: 128
  • pattern: [a-z0-9_](([a-z0-9_]+-)*([a-z0-9_]+))?

columnType -> (string) [required]

The data type of the column, which determines how the synthetic data generation algorithm processes and synthesizes values for this column.

Possible values:

  • CATEGORICAL
  • NUMERICAL

isPredictiveValue -> (boolean) [required]

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 -> (structure)

Evaluation scores that assess the quality and privacy characteristics of the generated synthetic data, providing metrics on data utility and privacy preservation.

dataPrivacyScores -> (structure) [required]

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) [required]

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.

Constraints:

  • min: 1
  • max: 1

(structure)

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) [required]

The version of the membership inference attack, which consists of the attack type and its version number, used to generate this privacy score.

Possible values:

  • DISTANCE_TO_CLOSEST_RECORD_V1

score -> (double) [required]

The numerical score representing the vulnerability to membership inference attacks.

Constraints:

  • min: 0.0
  • max: 1.0

createTime -> (timestamp)

The time at which the ML input channel was created.

updateTime -> (timestamp)

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.

Constraints:

  • min: 12
  • max: 12
  • pattern: [0-9]{12}
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