Class: Aws::CleanRoomsML::Client

Inherits:
Seahorse::Client::Base
  • Object
show all
Includes:
Aws::ClientStubs
Defined in:
lib/aws-sdk-cleanroomsml/client.rb

Overview

An API client for CleanRoomsML. To construct a client, you need to configure a ‘:region` and `:credentials`.

client = Aws::CleanRoomsML::Client.new(
  region: region_name,
  credentials: credentials,
  # ...
)

For details on configuring region and credentials see the [developer guide](/sdk-for-ruby/v3/developer-guide/setup-config.html).

See #initialize for a full list of supported configuration options.

Class Attribute Summary collapse

API Operations collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(options) ⇒ Client

Returns a new instance of Client.

Parameters:

  • options (Hash)

Options Hash (options):

  • :plugins (Array<Seahorse::Client::Plugin>) — default: []] —

    A list of plugins to apply to the client. Each plugin is either a class name or an instance of a plugin class.

  • :credentials (required, Aws::CredentialProvider) —

    Your AWS credentials used for authentication. This can be any class that includes and implements ‘Aws::CredentialProvider`, or instance of any one of the following classes:

    • ‘Aws::Credentials` - Used for configuring static, non-refreshing credentials.

    • ‘Aws::SharedCredentials` - Used for loading static credentials from a shared file, such as `~/.aws/config`.

    • ‘Aws::AssumeRoleCredentials` - Used when you need to assume a role.

    • ‘Aws::AssumeRoleWebIdentityCredentials` - Used when you need to assume a role after providing credentials via the web.

    • ‘Aws::SSOCredentials` - Used for loading credentials from AWS SSO using an access token generated from `aws login`.

    • ‘Aws::ProcessCredentials` - Used for loading credentials from a process that outputs to stdout.

    • ‘Aws::InstanceProfileCredentials` - Used for loading credentials from an EC2 IMDS on an EC2 instance.

    • ‘Aws::ECSCredentials` - Used for loading credentials from instances running in ECS.

    • ‘Aws::CognitoIdentityCredentials` - Used for loading credentials from the Cognito Identity service.

    When ‘:credentials` are not configured directly, the following locations will be searched for credentials:

    • ‘Aws.config`

    • The ‘:access_key_id`, `:secret_access_key`, `:session_token`, and `:account_id` options.

    • ‘ENV`, `ENV`, `ENV`, and `ENV`.

    • ‘~/.aws/credentials`

    • ‘~/.aws/config`

    • EC2/ECS IMDS instance profile - When used by default, the timeouts are very aggressive. Construct and pass an instance of ‘Aws::InstanceProfileCredentials` or `Aws::ECSCredentials` to enable retries and extended timeouts. Instance profile credential fetching can be disabled by setting `ENV` to `true`.

  • :region (required, String) —

    The AWS region to connect to. The configured ‘:region` is used to determine the service `:endpoint`. When not passed, a default `:region` is searched for in the following locations:

  • :access_key_id (String)
  • :account_id (String)
  • :active_endpoint_cache (Boolean) — default: false —

    When set to ‘true`, a thread polling for endpoints will be running in the background every 60 secs (default). Defaults to `false`.

  • :adaptive_retry_wait_to_fill (Boolean) — default: true —

    Used only in ‘adaptive` retry mode. When true, the request will sleep until there is sufficent client side capacity to retry the request. When false, the request will raise a `RetryCapacityNotAvailableError` and will not retry instead of sleeping.

  • :auth_scheme_preference (Array<String>) —

    A list of preferred authentication schemes to use when making a request. Supported values are: ‘sigv4`, `sigv4a`, `httpBearerAuth`, and `noAuth`. When set using `ENV` or in shared config as `auth_scheme_preference`, the value should be a comma-separated list.

  • :client_side_monitoring (Boolean) — default: false —

    When ‘true`, client-side metrics will be collected for all API requests from this client.

  • :client_side_monitoring_client_id (String) — default: "" —

    Allows you to provide an identifier for this client which will be attached to all generated client side metrics. Defaults to an empty string.

  • :client_side_monitoring_host (String) — default: "127.0.0.1" —

    Allows you to specify the DNS hostname or IPv4 or IPv6 address that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_port (Integer) — default: 31000 —

    Required for publishing client metrics. The port that the client side monitoring agent is running on, where client metrics will be published via UDP.

  • :client_side_monitoring_publisher (Aws::ClientSideMonitoring::Publisher) — default: Aws::ClientSideMonitoring::Publisher —

    Allows you to provide a custom client-side monitoring publisher class. By default, will use the Client Side Monitoring Agent Publisher.

  • :convert_params (Boolean) — default: true —

    When ‘true`, an attempt is made to coerce request parameters into the required types.

  • :correct_clock_skew (Boolean) — default: true —

    Used only in ‘standard` and `adaptive` retry modes. Specifies whether to apply a clock skew correction and retry requests with skewed client clocks.

  • :defaults_mode (String) — default: "legacy" —

    See DefaultsModeConfiguration for a list of the accepted modes and the configuration defaults that are included.

  • :disable_host_prefix_injection (Boolean) — default: false —

    When ‘true`, the SDK will not prepend the modeled host prefix to the endpoint.

  • :disable_request_compression (Boolean) — default: false —

    When set to ‘true’ the request body will not be compressed for supported operations.

  • :endpoint (String, URI::HTTPS, URI::HTTP) —

    Normally you should not configure the ‘:endpoint` option directly. This is normally constructed from the `:region` option. Configuring `:endpoint` is normally reserved for connecting to test or custom endpoints. The endpoint should be a URI formatted like:

    'http://example.com'
'https://example.com'
'http://example.com:123'
  • :endpoint_cache_max_entries (Integer) — default: 1000 —

    Used for the maximum size limit of the LRU cache storing endpoints data for endpoint discovery enabled operations. Defaults to 1000.

  • :endpoint_cache_max_threads (Integer) — default: 10 —

    Used for the maximum threads in use for polling endpoints to be cached, defaults to 10.

  • :endpoint_cache_poll_interval (Integer) — default: 60 —

    When :endpoint_discovery and :active_endpoint_cache is enabled, Use this option to config the time interval in seconds for making requests fetching endpoints information. Defaults to 60 sec.

  • :endpoint_discovery (Boolean) — default: false —

    When set to ‘true`, endpoint discovery will be enabled for operations when available.

  • :ignore_configured_endpoint_urls (Boolean) —

    Setting to true disables use of endpoint URLs provided via environment variables and the shared configuration file.

  • :log_formatter (Aws::Log::Formatter) — default: Aws::Log::Formatter.default —

    The log formatter.

  • :log_level (Symbol) — default: :info —

    The log level to send messages to the ‘:logger` at.

  • :logger (Logger) —

    The Logger instance to send log messages to. If this option is not set, logging will be disabled.

  • :max_attempts (Integer) — default: 3 —

    An integer representing the maximum number attempts that will be made for a single request, including the initial attempt. For example, setting this value to 5 will result in a request being retried up to 4 times. Used in ‘standard` and `adaptive` retry modes.

  • :profile (String) — default: "default" —

    Used when loading credentials from the shared credentials file at ‘HOME/.aws/credentials`. When not specified, ’default’ is used.

  • :request_checksum_calculation (String) — default: "when_supported" —

    Determines when a checksum will be calculated for request payloads. Values are:

    • ‘when_supported` - (default) When set, a checksum will be calculated for all request payloads of operations modeled with the `httpChecksum` trait where `requestChecksumRequired` is `true` and/or a `requestAlgorithmMember` is modeled.

    • ‘when_required` - When set, a checksum will only be calculated for request payloads of operations modeled with the `httpChecksum` trait where `requestChecksumRequired` is `true` or where a `requestAlgorithmMember` is modeled and supplied.

  • :request_min_compression_size_bytes (Integer) — default: 10240 —

    The minimum size in bytes that triggers compression for request bodies. The value must be non-negative integer value between 0 and 10485780 bytes inclusive.

  • :response_checksum_validation (String) — default: "when_supported" —

    Determines when checksum validation will be performed on response payloads. Values are:

    • ‘when_supported` - (default) When set, checksum validation is performed on all response payloads of operations modeled with the `httpChecksum` trait where `responseAlgorithms` is modeled, except when no modeled checksum algorithms are supported.

    • ‘when_required` - When set, checksum validation is not performed on response payloads of operations unless the checksum algorithm is supported and the `requestValidationModeMember` member is set to `ENABLED`.

  • :retry_backoff (Proc) —

    A proc or lambda used for backoff. Defaults to 2**retries * retry_base_delay. This option is only used in the ‘legacy` retry mode.

  • :retry_base_delay (Float) — default: 0.3 —

    The base delay in seconds used by the default backoff function. This option is only used in the ‘legacy` retry mode.

  • :retry_jitter (Symbol) — default: :none —

    A delay randomiser function used by the default backoff function. Some predefined functions can be referenced by name - :none, :equal, :full, otherwise a Proc that takes and returns a number. This option is only used in the ‘legacy` retry mode.

    @see www.awsarchitectureblog.com/2015/03/backoff.html

  • :retry_limit (Integer) — default: 3 —

    The maximum number of times to retry failed requests. Only ~ 500 level server errors and certain ~ 400 level client errors are retried. Generally, these are throttling errors, data checksum errors, networking errors, timeout errors, auth errors, endpoint discovery, and errors from expired credentials. This option is only used in the ‘legacy` retry mode.

  • :retry_max_delay (Integer) — default: 0 —

    The maximum number of seconds to delay between retries (0 for no limit) used by the default backoff function. This option is only used in the ‘legacy` retry mode.

  • :retry_mode (String) — default: "legacy" —

    Specifies which retry algorithm to use. Values are:

    • ‘legacy` - The pre-existing retry behavior. This is the default value if no retry mode is provided.

    • ‘standard` - A standardized set of retry rules across the AWS SDKs. This includes support for retry quotas, which limit the number of unsuccessful retries a client can make.

    • ‘adaptive` - A retry mode that includes all the functionality of `standard` mode along with automatic client side throttling.

  • :sdk_ua_app_id (String) —

    A unique and opaque application ID that is appended to the User-Agent header as app/sdk_ua_app_id. It should have a maximum length of 50. This variable is sourced from environment variable AWS_SDK_UA_APP_ID or the shared config profile attribute sdk_ua_app_id.

  • :secret_access_key (String)
  • :session_token (String)
  • :sigv4a_signing_region_set (Array) —

    A list of regions that should be signed with SigV4a signing. When not passed, a default ‘:sigv4a_signing_region_set` is searched for in the following locations:

  • :stub_responses (Boolean) — default: false —

    Causes the client to return stubbed responses. By default fake responses are generated and returned. You can specify the response data to return or errors to raise by calling ClientStubs#stub_responses. See ClientStubs for more information.

    ** Please note ** When response stubbing is enabled, no HTTP requests are made, and retries are disabled.

  • :telemetry_provider (Aws::Telemetry::TelemetryProviderBase) — default: Aws::Telemetry::NoOpTelemetryProvider —

    Allows you to provide a telemetry provider, which is used to emit telemetry data. By default, uses ‘NoOpTelemetryProvider` which will not record or emit any telemetry data. The SDK supports the following telemetry providers:

    • OpenTelemetry (OTel) - To use the OTel provider, install and require the

    ‘opentelemetry-sdk` gem and then, pass in an instance of a `Aws::Telemetry::OTelProvider` for telemetry provider.

  • :token_provider (Aws::TokenProvider) —

    Your Bearer token used for authentication. This can be any class that includes and implements ‘Aws::TokenProvider`, or instance of any one of the following classes:

    • ‘Aws::StaticTokenProvider` - Used for configuring static, non-refreshing tokens.

    • ‘Aws::SSOTokenProvider` - Used for loading tokens from AWS SSO using an access token generated from `aws login`.

    When ‘:token_provider` is not configured directly, the `Aws::TokenProviderChain` will be used to search for tokens configured for your profile in shared configuration files.

  • :use_dualstack_endpoint (Boolean) —

    When set to ‘true`, dualstack enabled endpoints (with `.aws` TLD) will be used if available.

  • :use_fips_endpoint (Boolean) —

    When set to ‘true`, fips compatible endpoints will be used if available. When a `fips` region is used, the region is normalized and this config is set to `true`.

  • :validate_params (Boolean) — default: true —

    When ‘true`, request parameters are validated before sending the request.

  • :endpoint_provider (Aws::CleanRoomsML::EndpointProvider) —

    The endpoint provider used to resolve endpoints. Any object that responds to ‘#resolve_endpoint(parameters)` where `parameters` is a Struct similar to `Aws::CleanRoomsML::EndpointParameters`.

  • :http_continue_timeout (Float) — default: 1 —

    The number of seconds to wait for a 100-continue response before sending the request body. This option has no effect unless the request has “Expect” header set to “100-continue”. Defaults to ‘nil` which disables this behaviour. This value can safely be set per request on the session.

  • :http_idle_timeout (Float) — default: 5 —

    The number of seconds a connection is allowed to sit idle before it is considered stale. Stale connections are closed and removed from the pool before making a request.

  • :http_open_timeout (Float) — default: 15 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_proxy (URI::HTTP, String) —

    A proxy to send requests through. Formatted like ‘proxy.com:123’.

  • :http_read_timeout (Float) — default: 60 —

    The default number of seconds to wait for response data. This value can safely be set per-request on the session.

  • :http_wire_trace (Boolean) — default: false —

    When ‘true`, HTTP debug output will be sent to the `:logger`.

  • :on_chunk_received (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the response body is received. It provides three arguments: the chunk, the number of bytes received, and the total number of bytes in the response (or nil if the server did not send a ‘content-length`).

  • :on_chunk_sent (Proc) —

    When a Proc object is provided, it will be used as callback when each chunk of the request body is sent. It provides three arguments: the chunk, the number of bytes read from the body, and the total number of bytes in the body.

  • :raise_response_errors (Boolean) — default: true —

    When ‘true`, response errors are raised.

  • :ssl_ca_bundle (String) —

    Full path to the SSL certificate authority bundle file that should be used when verifying peer certificates. If you do not pass ‘:ssl_ca_bundle` or `:ssl_ca_directory` the the system default will be used if available.

  • :ssl_ca_directory (String) —

    Full path of the directory that contains the unbundled SSL certificate authority files for verifying peer certificates. If you do not pass ‘:ssl_ca_bundle` or `:ssl_ca_directory` the the system default will be used if available.

  • :ssl_ca_store (String) —

    Sets the X509::Store to verify peer certificate.

  • :ssl_cert (OpenSSL::X509::Certificate) —

    Sets a client certificate when creating http connections.

  • :ssl_key (OpenSSL::PKey) —

    Sets a client key when creating http connections.

  • :ssl_timeout (Float) —

    Sets the SSL timeout in seconds

  • :ssl_verify_peer (Boolean) — default: true —

    When ‘true`, SSL peer certificates are verified when establishing a connection.



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 471

def initialize(*args)
  super
end

Class Attribute Details

.identifier ⇒ Object (readonly)

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4162

def identifier
  @identifier
end

Class Method Details

.errors_module ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4165

def errors_module
  Errors
end

Instance Method Details

#build_request(operation_name, params = {}) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Parameters:

  • params ({}) (defaults to: {}) 


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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4135

def build_request(operation_name, params = {})
  handlers = @handlers.for(operation_name)
  tracer = config.telemetry_provider.tracer_provider.tracer(
    Aws::Telemetry.module_to_tracer_name('Aws::CleanRoomsML')
  )
  context = Seahorse::Client::RequestContext.new(
    operation_name: operation_name,
    operation: config.api.operation(operation_name),
    client: self,
    params: params,
    config: config,
    tracer: tracer
  )
  context[:gem_name] = 'aws-sdk-cleanroomsml'
  context[:gem_version] = '1.47.0'
  Seahorse::Client::Request.new(handlers, context)
end

#cancel_trained_model(params = {}) ⇒ Struct

Submits a request to cancel the trained model job.

Examples:

Request syntax with placeholder values


resp = client.cancel_trained_model({
  membership_identifier: "UUID", # required
  trained_model_arn: "TrainedModelArn", # required
  version_identifier: "UUID",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the trained model job that you want to cancel.

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model job that you want to cancel.

  • :version_identifier (String) —

    The version identifier of the trained model to cancel. This parameter allows you to specify which version of the trained model you want to cancel when multiple versions exist.

    If ‘versionIdentifier` is not specified, the base model will be cancelled.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 508

def cancel_trained_model(params = {}, options = {})
  req = build_request(:cancel_trained_model, params)
  req.send_request(options)
end

#cancel_trained_model_inference_job(params = {}) ⇒ Struct

Submits a request to cancel a trained model inference job.

Examples:

Request syntax with placeholder values


resp = client.cancel_trained_model_inference_job({
  membership_identifier: "UUID", # required
  trained_model_inference_job_arn: "TrainedModelInferenceJobArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the trained model inference job that you want to cancel.

  • :trained_model_inference_job_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model inference job that you want to cancel.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 536

def cancel_trained_model_inference_job(params = {}, options = {})
  req = build_request(:cancel_trained_model_inference_job, params)
  req.send_request(options)
end

#create_audience_model(params = {}) ⇒ Types::CreateAudienceModelResponse

Defines the information necessary to create an audience model. An audience model is a machine learning model that Clean Rooms ML trains to measure similarity between users. Clean Rooms ML manages training and storing the audience model. The audience model can be used in multiple calls to the StartAudienceGenerationJob API.

Examples:

Request syntax with placeholder values


resp = client.create_audience_model({
  training_data_start_time: Time.now,
  training_data_end_time: Time.now,
  name: "NameString", # required
  training_dataset_arn: "TrainingDatasetArn", # required
  kms_key_arn: "KmsKeyArn",
  tags: {
    "TagKey" => "TagValue",
  },
  description: "ResourceDescription",
})

Response structure


resp.audience_model_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :training_data_start_time (Time, DateTime, Date, Integer, String) —

    The start date and time of the training window.

  • :training_data_end_time (Time, DateTime, Date, Integer, String) —

    The end date and time of the training window.

  • :name (required, String) —

    The name of the audience model resource.

  • :training_dataset_arn (required, String) —

    The Amazon Resource Name (ARN) of the training dataset for this audience model.

  • :kms_key_arn (String) —

    The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and the associated data.

  • :tags (Hash<String,String>) —

    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.

  • :description (String) —

    The description of the audience model.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 626

def create_audience_model(params = {}, options = {})
  req = build_request(:create_audience_model, params)
  req.send_request(options)
end

#create_configured_audience_model(params = {}) ⇒ Types::CreateConfiguredAudienceModelResponse

Defines the information necessary to create a configured audience model.

Examples:

Request syntax with placeholder values


resp = client.create_configured_audience_model({
  name: "NameString", # required
  audience_model_arn: "AudienceModelArn", # required
  output_config: { # required
    destination: { # required
      s3_destination: { # required
        s3_uri: "S3Path", # required
      },
    },
    role_arn: "IamRoleArn", # required
  },
  description: "ResourceDescription",
  shared_audience_metrics: ["ALL"], # required, accepts ALL, NONE
  min_matching_seed_size: 1,
  audience_size_config: {
    audience_size_type: "ABSOLUTE", # required, accepts ABSOLUTE, PERCENTAGE
    audience_size_bins: [1], # required
  },
  tags: {
    "TagKey" => "TagValue",
  },
  child_resource_tag_on_create_policy: "FROM_PARENT_RESOURCE", # accepts FROM_PARENT_RESOURCE, NONE
})

Response structure


resp.configured_audience_model_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name of the configured audience model.

  • :audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the audience model to use for the configured audience model.

  • :output_config (required, Types::ConfiguredAudienceModelOutputConfig) —

    Configure the Amazon S3 location and IAM Role for audiences created using this configured audience model. Each audience will have a unique location. The IAM Role must have ‘s3:PutObject` permission on the destination Amazon S3 location. If the destination is protected with Amazon S3 KMS-SSE, then the Role must also have the required KMS permissions.

  • :description (String) —

    The description of the configured audience model.

  • :shared_audience_metrics (required, Array<String>) —

    Whether audience metrics are shared.

  • :min_matching_seed_size (Integer) —

    The minimum number of users from the seed audience that must match with users in the training data of the audience model. The default value is 500.

  • :audience_size_config (Types::AudienceSizeConfig) —

    Configure the list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an ‘audienceSize` selected from this list. You can use the `ABSOLUTE` AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the `Percentage` AudienceSize to configure sizes in the range 1-100 percent.

  • :tags (Hash<String,String>) —

    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.

  • :child_resource_tag_on_create_policy (String) —

    Configure how the service tags audience generation jobs created using this configured audience model. If you specify ‘NONE`, the tags from the StartAudienceGenerationJob request determine the tags of the audience generation job. If you specify `FROM_PARENT_RESOURCE`, the audience generation job inherits the tags from the configured audience model, by default. Tags in the StartAudienceGenerationJob will override the default.

    When the client is in a different account than the configured audience model, the tags from the client are never applied to a resource in the caller’s account.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 752

def create_configured_audience_model(params = {}, options = {})
  req = build_request(:create_configured_audience_model, params)
  req.send_request(options)
end

#create_configured_model_algorithm(params = {}) ⇒ Types::CreateConfiguredModelAlgorithmResponse

Creates a configured model algorithm using a container image stored in an ECR repository.

Examples:

Request syntax with placeholder values


resp = client.create_configured_model_algorithm({
  name: "NameString", # required
  description: "ResourceDescription",
  role_arn: "IamRoleArn", # required
  training_container_config: {
    image_uri: "AlgorithmImage", # required
    entrypoint: ["ContainerEntrypointString"],
    arguments: ["ContainerArgument"],
    metric_definitions: [
      {
        name: "MetricName", # required
        regex: "MetricRegex", # required
      },
    ],
  },
  inference_container_config: {
    image_uri: "AlgorithmImage", # required
  },
  tags: {
    "TagKey" => "TagValue",
  },
  kms_key_arn: "KmsKeyArn",
})

Response structure


resp.configured_model_algorithm_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name of the configured model algorithm.

  • :description (String) —

    The description of the configured model algorithm.

  • :role_arn (required, String) —

    The Amazon Resource Name (ARN) of the role that is used to access the repository.

  • :training_container_config (Types::ContainerConfig) —

    Configuration information for the training container, including entrypoints and arguments.

  • :inference_container_config (Types::InferenceContainerConfig) —

    Configuration information for the inference container that is used when you run an inference job on a configured model algorithm.

  • :tags (Hash<String,String>) —

    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.

  • :kms_key_arn (String) —

    The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the configured ML model algorithm and associated data.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 853

def create_configured_model_algorithm(params = {}, options = {})
  req = build_request(:create_configured_model_algorithm, params)
  req.send_request(options)
end

#create_configured_model_algorithm_association(params = {}) ⇒ Types::CreateConfiguredModelAlgorithmAssociationResponse

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

Examples:

Request syntax with placeholder values


resp = client.create_configured_model_algorithm_association({
  membership_identifier: "UUID", # required
  configured_model_algorithm_arn: "ConfiguredModelAlgorithmArn", # required
  name: "NameString", # required
  description: "ResourceDescription",
  privacy_configuration: {
    policies: { # required
      trained_models: {
        container_logs: [
          {
            allowed_account_ids: ["String"], # required
            filter_pattern: "LogsConfigurationPolicyFilterPatternString",
            log_type: "ALL", # accepts ALL, ERROR_SUMMARY
            log_redaction_configuration: {
              entities_to_redact: ["ALL_PERSONALLY_IDENTIFIABLE_INFORMATION"], # required, accepts ALL_PERSONALLY_IDENTIFIABLE_INFORMATION, NUMBERS, CUSTOM
              custom_entity_config: {
                custom_data_identifiers: ["CustomDataIdentifier"], # required
              },
            },
          },
        ],
        container_metrics: {
          noise_level: "HIGH", # required, accepts HIGH, MEDIUM, LOW, NONE
        },
        max_artifact_size: {
          unit: "GB", # required, accepts GB
          value: 1.0, # required
        },
      },
      trained_model_exports: {
        max_size: { # required
          unit: "GB", # required, accepts GB
          value: 1.0, # required
        },
        files_to_export: ["MODEL"], # required, accepts MODEL, OUTPUT
      },
      trained_model_inference_jobs: {
        container_logs: [
          {
            allowed_account_ids: ["String"], # required
            filter_pattern: "LogsConfigurationPolicyFilterPatternString",
            log_type: "ALL", # accepts ALL, ERROR_SUMMARY
            log_redaction_configuration: {
              entities_to_redact: ["ALL_PERSONALLY_IDENTIFIABLE_INFORMATION"], # required, accepts ALL_PERSONALLY_IDENTIFIABLE_INFORMATION, NUMBERS, CUSTOM
              custom_entity_config: {
                custom_data_identifiers: ["CustomDataIdentifier"], # required
              },
            },
          },
        ],
        max_output_size: {
          unit: "GB", # required, accepts GB
          value: 1.0, # required
        },
      },
    },
  },
  tags: {
    "TagKey" => "TagValue",
  },
})

Response structure


resp.configured_model_algorithm_association_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

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

  • :configured_model_algorithm_arn (required, String) —

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

  • :name (required, String) —

    The name of the configured model algorithm association.

  • :description (String) —

    The description of the configured model algorithm association.

  • :privacy_configuration (Types::PrivacyConfiguration) —

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

  • :tags (Hash<String,String>) —

    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.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 988

def create_configured_model_algorithm_association(params = {}, options = {})
  req = build_request(:create_configured_model_algorithm_association, params)
  req.send_request(options)
end

#create_ml_input_channel(params = {}) ⇒ Types::CreateMLInputChannelResponse

Provides the information to create an ML input channel. An ML input channel is the result of a query that can be used for ML modeling.

Examples:

Request syntax with placeholder values


resp = client.create_ml_input_channel({
  membership_identifier: "UUID", # required
  configured_model_algorithm_associations: ["ConfiguredModelAlgorithmAssociationArn"], # required
  input_channel: { # required
    data_source: { # required
      protected_query_input_parameters: {
        sql_parameters: { # required
          query_string: "ProtectedQuerySQLParametersQueryStringString",
          analysis_template_arn: "AnalysisTemplateArn",
          parameters: {
            "ParameterName" => "ParameterValue",
          },
        },
        compute_configuration: {
          worker: {
            type: "CR.1X", # accepts CR.1X, CR.4X
            number: 1,
            properties: {
              spark: {
                "SparkPropertyKey" => "SparkPropertyValue",
              },
            },
          },
        },
        result_format: "CSV", # accepts CSV, PARQUET
      },
    },
    role_arn: "IamRoleArn", # required
  },
  name: "NameString", # required
  retention_in_days: 1, # required
  description: "ResourceDescription",
  kms_key_arn: "KmsKeyArn",
  tags: {
    "TagKey" => "TagValue",
  },
  payer_configuration: {
    compute_payer_account_id: "AccountId",
    synthetic_data_payer_account_id: "AccountId",
  },
})

Response structure


resp.ml_input_channel_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the member that is creating the ML input channel.

  • :configured_model_algorithm_associations (required, Array<String>) —

    The associated configured model algorithms that are necessary to create this ML input channel.

  • :input_channel (required, Types::InputChannel) —

    The input data that is used to create this ML input channel.

  • :name (required, String) —

    The name of the ML input channel.

  • :retention_in_days (required, Integer) —

    The number of days that the data in the ML input channel is retained.

  • :description (String) —

    The description of the ML input channel.

  • :kms_key_arn (String) —

    The Amazon Resource Name (ARN) of the KMS key that is used to access the input channel.

  • :tags (Hash<String,String>) —

    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.

  • :payer_configuration (Types::PayerConfiguration) —

    The payer configuration for the ML input channel. Determines which member account pays for compute and synthetic data costs.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1111

def create_ml_input_channel(params = {}, options = {})
  req = build_request(:create_ml_input_channel, params)
  req.send_request(options)
end

#create_trained_model(params = {}) ⇒ Types::CreateTrainedModelResponse

Creates a trained model from an associated configured model algorithm using data from any member of the collaboration.

Examples:

Request syntax with placeholder values


resp = client.create_trained_model({
  membership_identifier: "UUID", # required
  name: "NameString", # required
  configured_model_algorithm_association_arn: "ConfiguredModelAlgorithmAssociationArn", # required
  hyperparameters: {
    "HyperParametersKeyString" => "HyperParametersValueString",
  },
  environment: {
    "EnvironmentKeyString" => "EnvironmentValueString",
  },
  resource_config: { # required
    instance_count: 1,
    instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p4d.24xlarge, ml.p4de.24xlarge, ml.p5.48xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge, ml.g5.xlarge, ml.g5.2xlarge, ml.g5.4xlarge, ml.g5.8xlarge, ml.g5.16xlarge, ml.g5.12xlarge, ml.g5.24xlarge, ml.g5.48xlarge, ml.trn1.2xlarge, ml.trn1.32xlarge, ml.trn1n.32xlarge, ml.m6i.large, ml.m6i.xlarge, ml.m6i.2xlarge, ml.m6i.4xlarge, ml.m6i.8xlarge, ml.m6i.12xlarge, ml.m6i.16xlarge, ml.m6i.24xlarge, ml.m6i.32xlarge, ml.c6i.xlarge, ml.c6i.2xlarge, ml.c6i.8xlarge, ml.c6i.4xlarge, ml.c6i.12xlarge, ml.c6i.16xlarge, ml.c6i.24xlarge, ml.c6i.32xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.8xlarge, ml.r5d.12xlarge, ml.r5d.16xlarge, ml.r5d.24xlarge, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge, ml.c7i.large, ml.c7i.xlarge, ml.c7i.2xlarge, ml.c7i.4xlarge, ml.c7i.8xlarge, ml.c7i.12xlarge, ml.c7i.16xlarge, ml.c7i.24xlarge, ml.c7i.48xlarge, ml.m7i.large, ml.m7i.xlarge, ml.m7i.2xlarge, ml.m7i.4xlarge, ml.m7i.8xlarge, ml.m7i.12xlarge, ml.m7i.16xlarge, ml.m7i.24xlarge, ml.m7i.48xlarge, ml.r7i.large, ml.r7i.xlarge, ml.r7i.2xlarge, ml.r7i.4xlarge, ml.r7i.8xlarge, ml.r7i.12xlarge, ml.r7i.16xlarge, ml.r7i.24xlarge, ml.r7i.48xlarge, ml.g6.xlarge, ml.g6.2xlarge, ml.g6.4xlarge, ml.g6.8xlarge, ml.g6.12xlarge, ml.g6.16xlarge, ml.g6.24xlarge, ml.g6.48xlarge, ml.g6e.xlarge, ml.g6e.2xlarge, ml.g6e.4xlarge, ml.g6e.8xlarge, ml.g6e.12xlarge, ml.g6e.16xlarge, ml.g6e.24xlarge, ml.g6e.48xlarge, ml.p5en.48xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge
    volume_size_in_gb: 1, # required
  },
  stopping_condition: {
    max_runtime_in_seconds: 1,
  },
  incremental_training_data_channels: [
    {
      trained_model_arn: "TrainedModelArn", # required
      version_identifier: "UUID",
      channel_name: "ModelTrainingDataChannelName", # required
    },
  ],
  data_channels: [ # required
    {
      ml_input_channel_arn: "MLInputChannelArn", # required
      channel_name: "ModelTrainingDataChannelName", # required
      s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key
    },
  ],
  training_input_mode: "File", # accepts File, FastFile, Pipe
  description: "ResourceDescription",
  kms_key_arn: "KmsKeyArn",
  tags: {
    "TagKey" => "TagValue",
  },
  ml_model_training_payer_account_id: "AccountId",
})

Response structure


resp.trained_model_arn #=> String
resp.version_identifier #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the member that is creating the trained model.

  • :name (required, String) —

    The name of the trained model.

  • :configured_model_algorithm_association_arn (required, String) —

    The associated configured model algorithm used to train this model.

  • :hyperparameters (Hash<String,String>) —

    Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.

  • :environment (Hash<String,String>) —

    The environment variables to set in the Docker container.

  • :resource_config (required, Types::ResourceConfig) —

    Information about the EC2 resources that are used to train this model.

  • :stopping_condition (Types::StoppingCondition) —

    The criteria that is used to stop model training.

  • :incremental_training_data_channels (Array<Types::IncrementalTrainingDataChannel>) —

    Specifies the incremental training data channels for the trained model.

    Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

    Limit: Maximum of 20 channels total (including both ‘incrementalTrainingDataChannels` and `dataChannels`).

  • :data_channels (required, Array<Types::ModelTrainingDataChannel>) —

    Defines the data channels that are used as input for the trained model request.

    Limit: Maximum of 20 channels total (including both ‘dataChannels` and `incrementalTrainingDataChannels`).

  • :training_input_mode (String) —

    The input mode for accessing the training data. This parameter determines how the training data is made available to the training algorithm. Valid values are:

    • ‘File` - The training data is downloaded to the training instance and made available as files.

    • ‘FastFile` - The training data is streamed directly from Amazon S3 to the training algorithm, providing faster access for large datasets.

    • ‘Pipe` - The training data is streamed to the training algorithm using named pipes, which can improve performance for certain algorithms.

  • :description (String) —

    The description of the trained model.

  • :kms_key_arn (String) —

    The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and the associated data.

  • :tags (Hash<String,String>) —

    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.

  • :ml_model_training_payer_account_id (String) —

    The account ID of the member that is responsible for paying for model training costs.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1277

def create_trained_model(params = {}, options = {})
  req = build_request(:create_trained_model, params)
  req.send_request(options)
end

#create_training_dataset(params = {}) ⇒ Types::CreateTrainingDatasetResponse

Defines the information necessary to create a training dataset. In Clean Rooms ML, the ‘TrainingDataset` is metadata that points to a Glue table, which is read only during `AudienceModel` creation.

Examples:

Request syntax with placeholder values


resp = client.create_training_dataset({
  name: "NameString", # required
  role_arn: "IamRoleArn", # required
  training_data: [ # required
    {
      type: "INTERACTIONS", # required, accepts INTERACTIONS
      input_config: { # required
        schema: [ # required
          {
            column_name: "ColumnName", # required
            column_types: ["USER_ID"], # required, accepts USER_ID, ITEM_ID, TIMESTAMP, CATEGORICAL_FEATURE, NUMERICAL_FEATURE
          },
        ],
        data_source: { # required
          glue_data_source: { # required
            table_name: "GlueTableName", # required
            database_name: "GlueDatabaseName", # required
            catalog_id: "AccountId",
          },
        },
      },
    },
  ],
  tags: {
    "TagKey" => "TagValue",
  },
  description: "ResourceDescription",
})

Response structure


resp.training_dataset_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name of the training dataset. This name must be unique in your account and region.

  • :role_arn (required, String) —

    The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the ‘dataSource` field of each dataset.

    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.

  • :training_data (required, Array<Types::Dataset>) —

    An array of information that lists the Dataset objects, which specifies the dataset type and details on its location and schema. You must provide a role that has read access to these tables.

  • :tags (Hash<String,String>) —

    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.

  • :description (String) —

    The description of the training dataset.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1380

def create_training_dataset(params = {}, options = {})
  req = build_request(:create_training_dataset, params)
  req.send_request(options)
end

#delete_audience_generation_job(params = {}) ⇒ Struct

Deletes the specified audience generation job, and removes all data associated with the job.

Examples:

Request syntax with placeholder values


resp = client.delete_audience_generation_job({
  audience_generation_job_arn: "AudienceGenerationJobArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :audience_generation_job_arn (required, String) —

    The Amazon Resource Name (ARN) of the audience generation job that you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1404

def delete_audience_generation_job(params = {}, options = {})
  req = build_request(:delete_audience_generation_job, params)
  req.send_request(options)
end

#delete_audience_model(params = {}) ⇒ Struct

Specifies an audience model that you want to delete. You can’t delete an audience model if there are any configured audience models that depend on the audience model.

Examples:

Request syntax with placeholder values


resp = client.delete_audience_model({
  audience_model_arn: "AudienceModelArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the audience model that you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1429

def delete_audience_model(params = {}, options = {})
  req = build_request(:delete_audience_model, params)
  req.send_request(options)
end

#delete_configured_audience_model(params = {}) ⇒ Struct

Deletes the specified configured audience model. You can’t delete a configured audience model if there are any lookalike models that use the configured audience model. If you delete a configured audience model, it will be removed from any collaborations that it is associated to.

Examples:

Request syntax with placeholder values


resp = client.delete_configured_audience_model({
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_audience_model_arn (required, String) —

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

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1456

def delete_configured_audience_model(params = {}, options = {})
  req = build_request(:delete_configured_audience_model, params)
  req.send_request(options)
end

#delete_configured_audience_model_policy(params = {}) ⇒ Struct

Deletes the specified configured audience model policy.

Examples:

Request syntax with placeholder values


resp = client.delete_configured_audience_model_policy({
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured audience model policy that you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1479

def delete_configured_audience_model_policy(params = {}, options = {})
  req = build_request(:delete_configured_audience_model_policy, params)
  req.send_request(options)
end

#delete_configured_model_algorithm(params = {}) ⇒ Struct

Deletes a configured model algorithm.

Examples:

Request syntax with placeholder values


resp = client.delete_configured_model_algorithm({
  configured_model_algorithm_arn: "ConfiguredModelAlgorithmArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_model_algorithm_arn (required, String) —

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

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1502

def delete_configured_model_algorithm(params = {}, options = {})
  req = build_request(:delete_configured_model_algorithm, params)
  req.send_request(options)
end

#delete_configured_model_algorithm_association(params = {}) ⇒ Struct

Deletes a configured model algorithm association.

Examples:

Request syntax with placeholder values


resp = client.delete_configured_model_algorithm_association({
  configured_model_algorithm_association_arn: "ConfiguredModelAlgorithmAssociationArn", # required
  membership_identifier: "UUID", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_model_algorithm_association_arn (required, String) —

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

  • :membership_identifier (required, String) —

    The membership ID of the member that is deleting the configured model algorithm association.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1530

def delete_configured_model_algorithm_association(params = {}, options = {})
  req = build_request(:delete_configured_model_algorithm_association, params)
  req.send_request(options)
end

#delete_ml_configuration(params = {}) ⇒ Struct

Deletes a ML modeling configuration.

Examples:

Request syntax with placeholder values


resp = client.delete_ml_configuration({
  membership_identifier: "UUID", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the of the member that is deleting the ML modeling configuration.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1553

def delete_ml_configuration(params = {}, options = {})
  req = build_request(:delete_ml_configuration, params)
  req.send_request(options)
end

#delete_ml_input_channel_data(params = {}) ⇒ Struct

Provides the information necessary to delete an ML input channel.

Examples:

Request syntax with placeholder values


resp = client.delete_ml_input_channel_data({
  ml_input_channel_arn: "MLInputChannelArn", # required
  membership_identifier: "UUID", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :ml_input_channel_arn (required, String) —

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

  • :membership_identifier (required, String) —

    The membership ID of the membership that contains the ML input channel you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1581

def delete_ml_input_channel_data(params = {}, options = {})
  req = build_request(:delete_ml_input_channel_data, params)
  req.send_request(options)
end

#delete_trained_model_output(params = {}) ⇒ Struct

Deletes the model artifacts stored by the service.

Examples:

Request syntax with placeholder values


resp = client.delete_trained_model_output({
  trained_model_arn: "TrainedModelArn", # required
  membership_identifier: "UUID", # required
  version_identifier: "UUID",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model whose output you want to delete.

  • :membership_identifier (required, String) —

    The membership ID of the member that is deleting the trained model output.

  • :version_identifier (String) —

    The version identifier of the trained model to delete. If not specified, the operation will delete the base version of the trained model. When specified, only the particular version will be deleted.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1615

def delete_trained_model_output(params = {}, options = {})
  req = build_request(:delete_trained_model_output, params)
  req.send_request(options)
end

#delete_training_dataset(params = {}) ⇒ Struct

Specifies a training dataset that you want to delete. You can’t delete a training dataset if there are any audience models that depend on the training dataset. In Clean Rooms ML, the ‘TrainingDataset` is metadata that points to a Glue table, which is read only during `AudienceModel` creation. This action deletes the metadata.

Examples:

Request syntax with placeholder values


resp = client.delete_training_dataset({
  training_dataset_arn: "TrainingDatasetArn", # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :training_dataset_arn (required, String) —

    The Amazon Resource Name (ARN) of the training dataset that you want to delete.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1642

def delete_training_dataset(params = {}, options = {})
  req = build_request(:delete_training_dataset, params)
  req.send_request(options)
end

#get_audience_generation_job(params = {}) ⇒ Types::GetAudienceGenerationJobResponse

Returns information about an audience generation job.

Examples:

Request syntax with placeholder values


resp = client.get_audience_generation_job({
  audience_generation_job_arn: "AudienceGenerationJobArn", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.audience_generation_job_arn #=> String
resp.name #=> String
resp.description #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED"
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.configured_audience_model_arn #=> String
resp.seed_audience.data_source.s3_uri #=> String
resp.seed_audience.role_arn #=> String
resp.seed_audience.sql_parameters.query_string #=> String
resp.seed_audience.sql_parameters.analysis_template_arn #=> String
resp.seed_audience.sql_parameters.parameters #=> Hash
resp.seed_audience.sql_parameters.parameters["ParameterName"] #=> String
resp.seed_audience.sql_compute_configuration.worker.type #=> String, one of "CR.1X", "CR.4X"
resp.seed_audience.sql_compute_configuration.worker.number #=> Integer
resp.seed_audience.sql_compute_configuration.worker.properties.spark #=> Hash
resp.seed_audience.sql_compute_configuration.worker.properties.spark["SparkPropertyKey"] #=> String
resp.include_seed_in_output #=> Boolean
resp.collaboration_id #=> String
resp.metrics.relevance_metrics #=> Array
resp.metrics.relevance_metrics[0].audience_size.type #=> String, one of "ABSOLUTE", "PERCENTAGE"
resp.metrics.relevance_metrics[0].audience_size.value #=> Integer
resp.metrics.relevance_metrics[0].score #=> Float
resp.metrics.recall_metric #=> Float
resp.started_by #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp.protected_query_identifier #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :audience_generation_job_arn (required, String) —

    The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1714

def get_audience_generation_job(params = {}, options = {})
  req = build_request(:get_audience_generation_job, params)
  req.send_request(options)
end

#get_audience_model(params = {}) ⇒ Types::GetAudienceModelResponse

Returns information about an audience model

Examples:

Request syntax with placeholder values


resp = client.get_audience_model({
  audience_model_arn: "AudienceModelArn", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.training_data_start_time #=> Time
resp.training_data_end_time #=> Time
resp.audience_model_arn #=> String
resp.name #=> String
resp.training_dataset_arn #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED"
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.kms_key_arn #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp.description #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the audience model that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1767

def get_audience_model(params = {}, options = {})
  req = build_request(:get_audience_model, params)
  req.send_request(options)
end

#get_collaboration_configured_model_algorithm_association(params = {}) ⇒ Types::GetCollaborationConfiguredModelAlgorithmAssociationResponse

Returns information about the configured model algorithm association in a collaboration.

Examples:

Request syntax with placeholder values


resp = client.get_collaboration_configured_model_algorithm_association({
  configured_model_algorithm_association_arn: "ConfiguredModelAlgorithmAssociationArn", # required
  collaboration_identifier: "UUID", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.configured_model_algorithm_association_arn #=> String
resp.membership_identifier #=> String
resp.collaboration_identifier #=> String
resp.configured_model_algorithm_arn #=> String
resp.name #=> String
resp.description #=> String
resp. #=> String
resp.privacy_configuration.policies.trained_models.container_logs #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0]. #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0].[0] #=> String
resp.privacy_configuration.policies.trained_models.container_logs[0].filter_pattern #=> String
resp.privacy_configuration.policies.trained_models.container_logs[0].log_type #=> String, one of "ALL", "ERROR_SUMMARY"
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.entities_to_redact #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.entities_to_redact[0] #=> String, one of "ALL_PERSONALLY_IDENTIFIABLE_INFORMATION", "NUMBERS", "CUSTOM"
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers[0] #=> String
resp.privacy_configuration.policies.trained_models.container_metrics.noise_level #=> String, one of "HIGH", "MEDIUM", "LOW", "NONE"
resp.privacy_configuration.policies.trained_models.max_artifact_size.unit #=> String, one of "GB"
resp.privacy_configuration.policies.trained_models.max_artifact_size.value #=> Float
resp.privacy_configuration.policies.trained_model_exports.max_size.unit #=> String, one of "GB"
resp.privacy_configuration.policies.trained_model_exports.max_size.value #=> Float
resp.privacy_configuration.policies.trained_model_exports.files_to_export #=> Array
resp.privacy_configuration.policies.trained_model_exports.files_to_export[0] #=> String, one of "MODEL", "OUTPUT"
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0]. #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].[0] #=> String
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].filter_pattern #=> String
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_type #=> String, one of "ALL", "ERROR_SUMMARY"
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.entities_to_redact #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.entities_to_redact[0] #=> String, one of "ALL_PERSONALLY_IDENTIFIABLE_INFORMATION", "NUMBERS", "CUSTOM"
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers[0] #=> String
resp.privacy_configuration.policies.trained_model_inference_jobs.max_output_size.unit #=> String, one of "GB"
resp.privacy_configuration.policies.trained_model_inference_jobs.max_output_size.value #=> Float

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_model_algorithm_association_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

  • :collaboration_identifier (required, String) —

    The collaboration ID for the collaboration that contains the configured model algorithm association that you want to return information about.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1847

def get_collaboration_configured_model_algorithm_association(params = {}, options = {})
  req = build_request(:get_collaboration_configured_model_algorithm_association, params)
  req.send_request(options)
end

#get_collaboration_ml_input_channel(params = {}) ⇒ Types::GetCollaborationMLInputChannelResponse

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

Examples:

Request syntax with placeholder values


resp = client.get_collaboration_ml_input_channel({
  ml_input_channel_arn: "MLInputChannelArn", # required
  collaboration_identifier: "UUID", # required
})

Response structure


resp.membership_identifier #=> String
resp.collaboration_identifier #=> String
resp.ml_input_channel_arn #=> String
resp.name #=> String
resp.configured_model_algorithm_associations #=> Array
resp.configured_model_algorithm_associations[0] #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE"
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.retention_in_days #=> Integer
resp.number_of_records #=> Integer
resp.privacy_budgets.access_budgets #=> Array
resp.privacy_budgets.access_budgets[0].resource_arn #=> String
resp.privacy_budgets.access_budgets[0].details #=> Array
resp.privacy_budgets.access_budgets[0].details[0].start_time #=> Time
resp.privacy_budgets.access_budgets[0].details[0].end_time #=> Time
resp.privacy_budgets.access_budgets[0].details[0].remaining_budget #=> Integer
resp.privacy_budgets.access_budgets[0].details[0].budget #=> Integer
resp.privacy_budgets.access_budgets[0].details[0].budget_type #=> String, one of "CALENDAR_DAY", "CALENDAR_MONTH", "CALENDAR_WEEK", "LIFETIME"
resp.privacy_budgets.access_budgets[0].details[0].auto_refresh #=> String, one of "ENABLED", "DISABLED"
resp.privacy_budgets.access_budgets[0].aggregate_remaining_budget #=> Integer
resp.description #=> String
resp.synthetic_data_configuration.synthetic_data_parameters.epsilon #=> Float
resp.synthetic_data_configuration.synthetic_data_parameters.max_membership_inference_attack_score #=> Float
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping #=> Array
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping[0].column_name #=> String
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping[0].column_type #=> String, one of "CATEGORICAL", "NUMERICAL"
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping[0].is_predictive_value #=> Boolean
resp.synthetic_data_configuration.synthetic_data_evaluation_scores.data_privacy_scores.membership_inference_attack_scores #=> Array
resp.synthetic_data_configuration.synthetic_data_evaluation_scores.data_privacy_scores.membership_inference_attack_scores[0].attack_version #=> String, one of "DISTANCE_TO_CLOSEST_RECORD_V1"
resp.synthetic_data_configuration.synthetic_data_evaluation_scores.data_privacy_scores.membership_inference_attack_scores[0].score #=> Float
resp.payer_configuration. #=> String
resp.payer_configuration. #=> String
resp.create_time #=> Time
resp.update_time #=> Time
resp. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :ml_input_channel_arn (required, String) —

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

  • :collaboration_identifier (required, String) —

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

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 1932

def get_collaboration_ml_input_channel(params = {}, options = {})
  req = build_request(:get_collaboration_ml_input_channel, params)
  req.send_request(options)
end

#get_collaboration_trained_model(params = {}) ⇒ Types::GetCollaborationTrainedModelResponse

Returns information about a trained model in a collaboration.

Examples:

Request syntax with placeholder values


resp = client.get_collaboration_trained_model({
  trained_model_arn: "TrainedModelArn", # required
  collaboration_identifier: "UUID", # required
  version_identifier: "UUID",
})

Response structure


resp.membership_identifier #=> String
resp.collaboration_identifier #=> String
resp.trained_model_arn #=> String
resp.version_identifier #=> String
resp.incremental_training_data_channels #=> Array
resp.incremental_training_data_channels[0].channel_name #=> String
resp.incremental_training_data_channels[0].version_identifier #=> String
resp.incremental_training_data_channels[0].model_name #=> String
resp.name #=> String
resp.description #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED"
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.configured_model_algorithm_association_arn #=> String
resp.resource_config.instance_count #=> Integer
resp.resource_config.instance_type #=> String, one of "ml.m4.xlarge", "ml.m4.2xlarge", "ml.m4.4xlarge", "ml.m4.10xlarge", "ml.m4.16xlarge", "ml.g4dn.xlarge", "ml.g4dn.2xlarge", "ml.g4dn.4xlarge", "ml.g4dn.8xlarge", "ml.g4dn.12xlarge", "ml.g4dn.16xlarge", "ml.m5.large", "ml.m5.xlarge", "ml.m5.2xlarge", "ml.m5.4xlarge", "ml.m5.12xlarge", "ml.m5.24xlarge", "ml.c4.xlarge", "ml.c4.2xlarge", "ml.c4.4xlarge", "ml.c4.8xlarge", "ml.p2.xlarge", "ml.p2.8xlarge", "ml.p2.16xlarge", "ml.p4d.24xlarge", "ml.p4de.24xlarge", "ml.p5.48xlarge", "ml.c5.xlarge", "ml.c5.2xlarge", "ml.c5.4xlarge", "ml.c5.9xlarge", "ml.c5.18xlarge", "ml.c5n.xlarge", "ml.c5n.2xlarge", "ml.c5n.4xlarge", "ml.c5n.9xlarge", "ml.c5n.18xlarge", "ml.g5.xlarge", "ml.g5.2xlarge", "ml.g5.4xlarge", "ml.g5.8xlarge", "ml.g5.16xlarge", "ml.g5.12xlarge", "ml.g5.24xlarge", "ml.g5.48xlarge", "ml.trn1.2xlarge", "ml.trn1.32xlarge", "ml.trn1n.32xlarge", "ml.m6i.large", "ml.m6i.xlarge", "ml.m6i.2xlarge", "ml.m6i.4xlarge", "ml.m6i.8xlarge", "ml.m6i.12xlarge", "ml.m6i.16xlarge", "ml.m6i.24xlarge", "ml.m6i.32xlarge", "ml.c6i.xlarge", "ml.c6i.2xlarge", "ml.c6i.8xlarge", "ml.c6i.4xlarge", "ml.c6i.12xlarge", "ml.c6i.16xlarge", "ml.c6i.24xlarge", "ml.c6i.32xlarge", "ml.r5d.large", "ml.r5d.xlarge", "ml.r5d.2xlarge", "ml.r5d.4xlarge", "ml.r5d.8xlarge", "ml.r5d.12xlarge", "ml.r5d.16xlarge", "ml.r5d.24xlarge", "ml.t3.medium", "ml.t3.large", "ml.t3.xlarge", "ml.t3.2xlarge", "ml.r5.large", "ml.r5.xlarge", "ml.r5.2xlarge", "ml.r5.4xlarge", "ml.r5.8xlarge", "ml.r5.12xlarge", "ml.r5.16xlarge", "ml.r5.24xlarge", "ml.c7i.large", "ml.c7i.xlarge", "ml.c7i.2xlarge", "ml.c7i.4xlarge", "ml.c7i.8xlarge", "ml.c7i.12xlarge", "ml.c7i.16xlarge", "ml.c7i.24xlarge", "ml.c7i.48xlarge", "ml.m7i.large", "ml.m7i.xlarge", "ml.m7i.2xlarge", "ml.m7i.4xlarge", "ml.m7i.8xlarge", "ml.m7i.12xlarge", "ml.m7i.16xlarge", "ml.m7i.24xlarge", "ml.m7i.48xlarge", "ml.r7i.large", "ml.r7i.xlarge", "ml.r7i.2xlarge", "ml.r7i.4xlarge", "ml.r7i.8xlarge", "ml.r7i.12xlarge", "ml.r7i.16xlarge", "ml.r7i.24xlarge", "ml.r7i.48xlarge", "ml.g6.xlarge", "ml.g6.2xlarge", "ml.g6.4xlarge", "ml.g6.8xlarge", "ml.g6.12xlarge", "ml.g6.16xlarge", "ml.g6.24xlarge", "ml.g6.48xlarge", "ml.g6e.xlarge", "ml.g6e.2xlarge", "ml.g6e.4xlarge", "ml.g6e.8xlarge", "ml.g6e.12xlarge", "ml.g6e.16xlarge", "ml.g6e.24xlarge", "ml.g6e.48xlarge", "ml.p5en.48xlarge", "ml.p3.2xlarge", "ml.p3.8xlarge", "ml.p3.16xlarge", "ml.p3dn.24xlarge"
resp.resource_config.volume_size_in_gb #=> Integer
resp.training_input_mode #=> String, one of "File", "FastFile", "Pipe"
resp.stopping_condition.max_runtime_in_seconds #=> Integer
resp.metrics_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.metrics_status_details #=> String
resp.logs_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.logs_status_details #=> String
resp.training_container_image_digest #=> String
resp. #=> String
resp.create_time #=> Time
resp.update_time #=> Time
resp. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model that you want to return information about.

  • :collaboration_identifier (required, String) —

    The collaboration ID that contains the trained model that you want to return information about.

  • :version_identifier (String) —

    The version identifier of the trained model to retrieve. If not specified, the operation returns information about the latest version of the trained model.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2020

def get_collaboration_trained_model(params = {}, options = {})
  req = build_request(:get_collaboration_trained_model, params)
  req.send_request(options)
end

#get_configured_audience_model(params = {}) ⇒ Types::GetConfiguredAudienceModelResponse

Returns information about a specified configured audience model.

Examples:

Request syntax with placeholder values


resp = client.get_configured_audience_model({
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.configured_audience_model_arn #=> String
resp.name #=> String
resp.audience_model_arn #=> String
resp.output_config.destination.s3_destination.s3_uri #=> String
resp.output_config.role_arn #=> String
resp.description #=> String
resp.status #=> String, one of "ACTIVE"
resp.shared_audience_metrics #=> Array
resp.shared_audience_metrics[0] #=> String, one of "ALL", "NONE"
resp.min_matching_seed_size #=> Integer
resp.audience_size_config.audience_size_type #=> String, one of "ABSOLUTE", "PERCENTAGE"
resp.audience_size_config.audience_size_bins #=> Array
resp.audience_size_config.audience_size_bins[0] #=> Integer
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp.child_resource_tag_on_create_policy #=> String, one of "FROM_PARENT_RESOURCE", "NONE"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2078

def get_configured_audience_model(params = {}, options = {})
  req = build_request(:get_configured_audience_model, params)
  req.send_request(options)
end

#get_configured_audience_model_policy(params = {}) ⇒ Types::GetConfiguredAudienceModelPolicyResponse

Returns information about a configured audience model policy.

Examples:

Request syntax with placeholder values


resp = client.get_configured_audience_model_policy({
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
})

Response structure


resp.configured_audience_model_arn #=> String
resp.configured_audience_model_policy #=> String
resp.policy_hash #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2111

def get_configured_audience_model_policy(params = {}, options = {})
  req = build_request(:get_configured_audience_model_policy, params)
  req.send_request(options)
end

#get_configured_model_algorithm(params = {}) ⇒ Types::GetConfiguredModelAlgorithmResponse

Returns information about a configured model algorithm.

Examples:

Request syntax with placeholder values


resp = client.get_configured_model_algorithm({
  configured_model_algorithm_arn: "ConfiguredModelAlgorithmArn", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.configured_model_algorithm_arn #=> String
resp.name #=> String
resp.training_container_config.image_uri #=> String
resp.training_container_config.entrypoint #=> Array
resp.training_container_config.entrypoint[0] #=> String
resp.training_container_config.arguments #=> Array
resp.training_container_config.arguments[0] #=> String
resp.training_container_config.metric_definitions #=> Array
resp.training_container_config.metric_definitions[0].name #=> String
resp.training_container_config.metric_definitions[0].regex #=> String
resp.inference_container_config.image_uri #=> String
resp.role_arn #=> String
resp.description #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp.kms_key_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_model_algorithm_arn (required, String) —

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

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2166

def get_configured_model_algorithm(params = {}, options = {})
  req = build_request(:get_configured_model_algorithm, params)
  req.send_request(options)
end

#get_configured_model_algorithm_association(params = {}) ⇒ Types::GetConfiguredModelAlgorithmAssociationResponse

Returns information about a configured model algorithm association.

Examples:

Request syntax with placeholder values


resp = client.get_configured_model_algorithm_association({
  configured_model_algorithm_association_arn: "ConfiguredModelAlgorithmAssociationArn", # required
  membership_identifier: "UUID", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.configured_model_algorithm_association_arn #=> String
resp.membership_identifier #=> String
resp.collaboration_identifier #=> String
resp.configured_model_algorithm_arn #=> String
resp.name #=> String
resp.privacy_configuration.policies.trained_models.container_logs #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0]. #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0].[0] #=> String
resp.privacy_configuration.policies.trained_models.container_logs[0].filter_pattern #=> String
resp.privacy_configuration.policies.trained_models.container_logs[0].log_type #=> String, one of "ALL", "ERROR_SUMMARY"
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.entities_to_redact #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.entities_to_redact[0] #=> String, one of "ALL_PERSONALLY_IDENTIFIABLE_INFORMATION", "NUMBERS", "CUSTOM"
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers #=> Array
resp.privacy_configuration.policies.trained_models.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers[0] #=> String
resp.privacy_configuration.policies.trained_models.container_metrics.noise_level #=> String, one of "HIGH", "MEDIUM", "LOW", "NONE"
resp.privacy_configuration.policies.trained_models.max_artifact_size.unit #=> String, one of "GB"
resp.privacy_configuration.policies.trained_models.max_artifact_size.value #=> Float
resp.privacy_configuration.policies.trained_model_exports.max_size.unit #=> String, one of "GB"
resp.privacy_configuration.policies.trained_model_exports.max_size.value #=> Float
resp.privacy_configuration.policies.trained_model_exports.files_to_export #=> Array
resp.privacy_configuration.policies.trained_model_exports.files_to_export[0] #=> String, one of "MODEL", "OUTPUT"
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0]. #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].[0] #=> String
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].filter_pattern #=> String
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_type #=> String, one of "ALL", "ERROR_SUMMARY"
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.entities_to_redact #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.entities_to_redact[0] #=> String, one of "ALL_PERSONALLY_IDENTIFIABLE_INFORMATION", "NUMBERS", "CUSTOM"
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers #=> Array
resp.privacy_configuration.policies.trained_model_inference_jobs.container_logs[0].log_redaction_configuration.custom_entity_config.custom_data_identifiers[0] #=> String
resp.privacy_configuration.policies.trained_model_inference_jobs.max_output_size.unit #=> String, one of "GB"
resp.privacy_configuration.policies.trained_model_inference_jobs.max_output_size.value #=> Float
resp.description #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_model_algorithm_association_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

  • :membership_identifier (required, String) —

    The membership ID of the member that created the configured model algorithm association.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2245

def get_configured_model_algorithm_association(params = {}, options = {})
  req = build_request(:get_configured_model_algorithm_association, params)
  req.send_request(options)
end

#get_ml_configuration(params = {}) ⇒ Types::GetMLConfigurationResponse

Returns information about a specific ML configuration.

Examples:

Request syntax with placeholder values


resp = client.get_ml_configuration({
  membership_identifier: "UUID", # required
})

Response structure


resp.membership_identifier #=> String
resp.default_output_location.destination.s3_destination.s3_uri #=> String
resp.default_output_location.role_arn #=> String
resp.create_time #=> Time
resp.update_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the member that owns the ML configuration you want to return information about.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2281

def get_ml_configuration(params = {}, options = {})
  req = build_request(:get_ml_configuration, params)
  req.send_request(options)
end

#get_ml_input_channel(params = {}) ⇒ Types::GetMLInputChannelResponse

Returns information about an ML input channel.

Examples:

Request syntax with placeholder values


resp = client.get_ml_input_channel({
  ml_input_channel_arn: "MLInputChannelArn", # required
  membership_identifier: "UUID", # required
})

Response structure


resp.membership_identifier #=> String
resp.collaboration_identifier #=> String
resp.ml_input_channel_arn #=> String
resp.name #=> String
resp.configured_model_algorithm_associations #=> Array
resp.configured_model_algorithm_associations[0] #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE"
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.retention_in_days #=> Integer
resp.number_of_records #=> Integer
resp.privacy_budgets.access_budgets #=> Array
resp.privacy_budgets.access_budgets[0].resource_arn #=> String
resp.privacy_budgets.access_budgets[0].details #=> Array
resp.privacy_budgets.access_budgets[0].details[0].start_time #=> Time
resp.privacy_budgets.access_budgets[0].details[0].end_time #=> Time
resp.privacy_budgets.access_budgets[0].details[0].remaining_budget #=> Integer
resp.privacy_budgets.access_budgets[0].details[0].budget #=> Integer
resp.privacy_budgets.access_budgets[0].details[0].budget_type #=> String, one of "CALENDAR_DAY", "CALENDAR_MONTH", "CALENDAR_WEEK", "LIFETIME"
resp.privacy_budgets.access_budgets[0].details[0].auto_refresh #=> String, one of "ENABLED", "DISABLED"
resp.privacy_budgets.access_budgets[0].aggregate_remaining_budget #=> Integer
resp.description #=> String
resp.synthetic_data_configuration.synthetic_data_parameters.epsilon #=> Float
resp.synthetic_data_configuration.synthetic_data_parameters.max_membership_inference_attack_score #=> Float
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping #=> Array
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping[0].column_name #=> String
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping[0].column_type #=> String, one of "CATEGORICAL", "NUMERICAL"
resp.synthetic_data_configuration.synthetic_data_parameters.column_classification.column_mapping[0].is_predictive_value #=> Boolean
resp.synthetic_data_configuration.synthetic_data_evaluation_scores.data_privacy_scores.membership_inference_attack_scores #=> Array
resp.synthetic_data_configuration.synthetic_data_evaluation_scores.data_privacy_scores.membership_inference_attack_scores[0].attack_version #=> String, one of "DISTANCE_TO_CLOSEST_RECORD_V1"
resp.synthetic_data_configuration.synthetic_data_evaluation_scores.data_privacy_scores.membership_inference_attack_scores[0].score #=> Float
resp.payer_configuration. #=> String
resp.payer_configuration. #=> String
resp.create_time #=> Time
resp.update_time #=> Time
resp.input_channel.data_source.protected_query_input_parameters.sql_parameters.query_string #=> String
resp.input_channel.data_source.protected_query_input_parameters.sql_parameters.analysis_template_arn #=> String
resp.input_channel.data_source.protected_query_input_parameters.sql_parameters.parameters #=> Hash
resp.input_channel.data_source.protected_query_input_parameters.sql_parameters.parameters["ParameterName"] #=> String
resp.input_channel.data_source.protected_query_input_parameters.compute_configuration.worker.type #=> String, one of "CR.1X", "CR.4X"
resp.input_channel.data_source.protected_query_input_parameters.compute_configuration.worker.number #=> Integer
resp.input_channel.data_source.protected_query_input_parameters.compute_configuration.worker.properties.spark #=> Hash
resp.input_channel.data_source.protected_query_input_parameters.compute_configuration.worker.properties.spark["SparkPropertyKey"] #=> String
resp.input_channel.data_source.protected_query_input_parameters.result_format #=> String, one of "CSV", "PARQUET"
resp.input_channel.role_arn #=> String
resp.protected_query_identifier #=> String
resp.number_of_files #=> Float
resp.size_in_gb #=> Float
resp.kms_key_arn #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :ml_input_channel_arn (required, String) —

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

  • :membership_identifier (required, String) —

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

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2385

def get_ml_input_channel(params = {}, options = {})
  req = build_request(:get_ml_input_channel, params)
  req.send_request(options)
end

#get_trained_model(params = {}) ⇒ Types::GetTrainedModelResponse

Returns information about a trained model.

Examples:

Request syntax with placeholder values


resp = client.get_trained_model({
  trained_model_arn: "TrainedModelArn", # required
  membership_identifier: "UUID", # required
  version_identifier: "UUID",
})

Response structure


resp.membership_identifier #=> String
resp.collaboration_identifier #=> String
resp.trained_model_arn #=> String
resp.version_identifier #=> String
resp.incremental_training_data_channels #=> Array
resp.incremental_training_data_channels[0].channel_name #=> String
resp.incremental_training_data_channels[0].version_identifier #=> String
resp.incremental_training_data_channels[0].model_name #=> String
resp.name #=> String
resp.description #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED"
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.configured_model_algorithm_association_arn #=> String
resp.resource_config.instance_count #=> Integer
resp.resource_config.instance_type #=> String, one of "ml.m4.xlarge", "ml.m4.2xlarge", "ml.m4.4xlarge", "ml.m4.10xlarge", "ml.m4.16xlarge", "ml.g4dn.xlarge", "ml.g4dn.2xlarge", "ml.g4dn.4xlarge", "ml.g4dn.8xlarge", "ml.g4dn.12xlarge", "ml.g4dn.16xlarge", "ml.m5.large", "ml.m5.xlarge", "ml.m5.2xlarge", "ml.m5.4xlarge", "ml.m5.12xlarge", "ml.m5.24xlarge", "ml.c4.xlarge", "ml.c4.2xlarge", "ml.c4.4xlarge", "ml.c4.8xlarge", "ml.p2.xlarge", "ml.p2.8xlarge", "ml.p2.16xlarge", "ml.p4d.24xlarge", "ml.p4de.24xlarge", "ml.p5.48xlarge", "ml.c5.xlarge", "ml.c5.2xlarge", "ml.c5.4xlarge", "ml.c5.9xlarge", "ml.c5.18xlarge", "ml.c5n.xlarge", "ml.c5n.2xlarge", "ml.c5n.4xlarge", "ml.c5n.9xlarge", "ml.c5n.18xlarge", "ml.g5.xlarge", "ml.g5.2xlarge", "ml.g5.4xlarge", "ml.g5.8xlarge", "ml.g5.16xlarge", "ml.g5.12xlarge", "ml.g5.24xlarge", "ml.g5.48xlarge", "ml.trn1.2xlarge", "ml.trn1.32xlarge", "ml.trn1n.32xlarge", "ml.m6i.large", "ml.m6i.xlarge", "ml.m6i.2xlarge", "ml.m6i.4xlarge", "ml.m6i.8xlarge", "ml.m6i.12xlarge", "ml.m6i.16xlarge", "ml.m6i.24xlarge", "ml.m6i.32xlarge", "ml.c6i.xlarge", "ml.c6i.2xlarge", "ml.c6i.8xlarge", "ml.c6i.4xlarge", "ml.c6i.12xlarge", "ml.c6i.16xlarge", "ml.c6i.24xlarge", "ml.c6i.32xlarge", "ml.r5d.large", "ml.r5d.xlarge", "ml.r5d.2xlarge", "ml.r5d.4xlarge", "ml.r5d.8xlarge", "ml.r5d.12xlarge", "ml.r5d.16xlarge", "ml.r5d.24xlarge", "ml.t3.medium", "ml.t3.large", "ml.t3.xlarge", "ml.t3.2xlarge", "ml.r5.large", "ml.r5.xlarge", "ml.r5.2xlarge", "ml.r5.4xlarge", "ml.r5.8xlarge", "ml.r5.12xlarge", "ml.r5.16xlarge", "ml.r5.24xlarge", "ml.c7i.large", "ml.c7i.xlarge", "ml.c7i.2xlarge", "ml.c7i.4xlarge", "ml.c7i.8xlarge", "ml.c7i.12xlarge", "ml.c7i.16xlarge", "ml.c7i.24xlarge", "ml.c7i.48xlarge", "ml.m7i.large", "ml.m7i.xlarge", "ml.m7i.2xlarge", "ml.m7i.4xlarge", "ml.m7i.8xlarge", "ml.m7i.12xlarge", "ml.m7i.16xlarge", "ml.m7i.24xlarge", "ml.m7i.48xlarge", "ml.r7i.large", "ml.r7i.xlarge", "ml.r7i.2xlarge", "ml.r7i.4xlarge", "ml.r7i.8xlarge", "ml.r7i.12xlarge", "ml.r7i.16xlarge", "ml.r7i.24xlarge", "ml.r7i.48xlarge", "ml.g6.xlarge", "ml.g6.2xlarge", "ml.g6.4xlarge", "ml.g6.8xlarge", "ml.g6.12xlarge", "ml.g6.16xlarge", "ml.g6.24xlarge", "ml.g6.48xlarge", "ml.g6e.xlarge", "ml.g6e.2xlarge", "ml.g6e.4xlarge", "ml.g6e.8xlarge", "ml.g6e.12xlarge", "ml.g6e.16xlarge", "ml.g6e.24xlarge", "ml.g6e.48xlarge", "ml.p5en.48xlarge", "ml.p3.2xlarge", "ml.p3.8xlarge", "ml.p3.16xlarge", "ml.p3dn.24xlarge"
resp.resource_config.volume_size_in_gb #=> Integer
resp.training_input_mode #=> String, one of "File", "FastFile", "Pipe"
resp.stopping_condition.max_runtime_in_seconds #=> Integer
resp.metrics_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.metrics_status_details #=> String
resp.logs_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.logs_status_details #=> String
resp.training_container_image_digest #=> String
resp. #=> String
resp.create_time #=> Time
resp.update_time #=> Time
resp.hyperparameters #=> Hash
resp.hyperparameters["HyperParametersKeyString"] #=> String
resp.environment #=> Hash
resp.environment["EnvironmentKeyString"] #=> String
resp.kms_key_arn #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp.data_channels #=> Array
resp.data_channels[0].ml_input_channel_arn #=> String
resp.data_channels[0].channel_name #=> String
resp.data_channels[0].s3_data_distribution_type #=> String, one of "FullyReplicated", "ShardedByS3Key"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model that you are interested in.

  • :membership_identifier (required, String) —

    The membership ID of the member that created the trained model that you are interested in.

  • :version_identifier (String) —

    The version identifier of the trained model to retrieve. If not specified, the operation returns information about the latest version of the trained model.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2487

def get_trained_model(params = {}, options = {})
  req = build_request(:get_trained_model, params)
  req.send_request(options)
end

#get_trained_model_inference_job(params = {}) ⇒ Types::GetTrainedModelInferenceJobResponse

Returns information about a trained model inference job.

Examples:

Request syntax with placeholder values


resp = client.get_trained_model_inference_job({
  membership_identifier: "UUID", # required
  trained_model_inference_job_arn: "TrainedModelInferenceJobArn", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.trained_model_inference_job_arn #=> String
resp.configured_model_algorithm_association_arn #=> String
resp.name #=> String
resp.status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED", "INACTIVE"
resp.trained_model_arn #=> String
resp.trained_model_version_identifier #=> String
resp.resource_config.instance_type #=> String, one of "ml.r7i.48xlarge", "ml.r6i.16xlarge", "ml.m6i.xlarge", "ml.m5.4xlarge", "ml.p2.xlarge", "ml.m4.16xlarge", "ml.r7i.16xlarge", "ml.m7i.xlarge", "ml.m6i.12xlarge", "ml.r7i.8xlarge", "ml.r7i.large", "ml.m7i.12xlarge", "ml.m6i.24xlarge", "ml.m7i.24xlarge", "ml.r6i.8xlarge", "ml.r6i.large", "ml.g5.2xlarge", "ml.m5.large", "ml.m7i.48xlarge", "ml.m6i.16xlarge", "ml.p2.16xlarge", "ml.g5.4xlarge", "ml.m7i.16xlarge", "ml.c4.2xlarge", "ml.c5.2xlarge", "ml.c6i.32xlarge", "ml.c4.4xlarge", "ml.g5.8xlarge", "ml.c6i.xlarge", "ml.c5.4xlarge", "ml.g4dn.xlarge", "ml.c7i.xlarge", "ml.c6i.12xlarge", "ml.g4dn.12xlarge", "ml.c7i.12xlarge", "ml.c6i.24xlarge", "ml.g4dn.2xlarge", "ml.c7i.24xlarge", "ml.c7i.2xlarge", "ml.c4.8xlarge", "ml.c6i.2xlarge", "ml.g4dn.4xlarge", "ml.c7i.48xlarge", "ml.c7i.4xlarge", "ml.c6i.16xlarge", "ml.c5.9xlarge", "ml.g4dn.16xlarge", "ml.c7i.16xlarge", "ml.c6i.4xlarge", "ml.c5.xlarge", "ml.c4.xlarge", "ml.g4dn.8xlarge", "ml.c7i.8xlarge", "ml.c7i.large", "ml.g5.xlarge", "ml.c6i.8xlarge", "ml.c6i.large", "ml.g5.12xlarge", "ml.g5.24xlarge", "ml.m7i.2xlarge", "ml.c5.18xlarge", "ml.g5.48xlarge", "ml.m6i.2xlarge", "ml.g5.16xlarge", "ml.m7i.4xlarge", "ml.r6i.32xlarge", "ml.m6i.4xlarge", "ml.m5.xlarge", "ml.m4.10xlarge", "ml.r6i.xlarge", "ml.m5.12xlarge", "ml.m4.xlarge", "ml.r7i.2xlarge", "ml.r7i.xlarge", "ml.r6i.12xlarge", "ml.m5.24xlarge", "ml.r7i.12xlarge", "ml.m7i.8xlarge", "ml.m7i.large", "ml.r6i.24xlarge", "ml.r6i.2xlarge", "ml.m4.2xlarge", "ml.r7i.24xlarge", "ml.r7i.4xlarge", "ml.m6i.8xlarge", "ml.m6i.large", "ml.m5.2xlarge", "ml.p2.8xlarge", "ml.r6i.4xlarge", "ml.m6i.32xlarge", "ml.m4.4xlarge", "ml.p3.16xlarge", "ml.p3.2xlarge", "ml.p3.8xlarge"
resp.resource_config.instance_count #=> Integer
resp.output_configuration.accept #=> String
resp.output_configuration.members #=> Array
resp.output_configuration.members[0]. #=> String
resp.membership_identifier #=> String
resp.data_source.ml_input_channel_arn #=> String
resp.container_execution_parameters.max_payload_in_mb #=> Integer
resp.status_details.status_code #=> String
resp.status_details.message #=> String
resp.description #=> String
resp.inference_container_image_digest #=> String
resp.environment #=> Hash
resp.environment["InferenceEnvironmentMapKeyString"] #=> String
resp.kms_key_arn #=> String
resp.metrics_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.metrics_status_details #=> String
resp.logs_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.logs_status_details #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    Provides the membership ID of the membership that contains the trained model inference job that you are interested in.

  • :trained_model_inference_job_arn (required, String) —

    Provides the Amazon Resource Name (ARN) of the trained model inference job that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2573

def get_trained_model_inference_job(params = {}, options = {})
  req = build_request(:get_trained_model_inference_job, params)
  req.send_request(options)
end

#get_training_dataset(params = {}) ⇒ Types::GetTrainingDatasetResponse

Returns information about a training dataset.

Examples:

Request syntax with placeholder values


resp = client.get_training_dataset({
  training_dataset_arn: "TrainingDatasetArn", # required
})

Response structure


resp.create_time #=> Time
resp.update_time #=> Time
resp.training_dataset_arn #=> String
resp.name #=> String
resp.training_data #=> Array
resp.training_data[0].type #=> String, one of "INTERACTIONS"
resp.training_data[0].input_config.schema #=> Array
resp.training_data[0].input_config.schema[0].column_name #=> String
resp.training_data[0].input_config.schema[0].column_types #=> Array
resp.training_data[0].input_config.schema[0].column_types[0] #=> String, one of "USER_ID", "ITEM_ID", "TIMESTAMP", "CATEGORICAL_FEATURE", "NUMERICAL_FEATURE"
resp.training_data[0].input_config.data_source.glue_data_source.table_name #=> String
resp.training_data[0].input_config.data_source.glue_data_source.database_name #=> String
resp.training_data[0].input_config.data_source.glue_data_source.catalog_id #=> String
resp.status #=> String, one of "ACTIVE"
resp.role_arn #=> String
resp.tags #=> Hash
resp.tags["TagKey"] #=> String
resp.description #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :training_dataset_arn (required, String) —

    The Amazon Resource Name (ARN) of the training dataset that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2627

def get_training_dataset(params = {}, options = {})
  req = build_request(:get_training_dataset, params)
  req.send_request(options)
end

#list_audience_export_jobs(params = {}) ⇒ Types::ListAudienceExportJobsResponse

Returns a list of the audience export jobs.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_audience_export_jobs({
  next_token: "NextToken",
  max_results: 1,
  audience_generation_job_arn: "AudienceGenerationJobArn",
})

Response structure


resp.next_token #=> String
resp.audience_export_jobs #=> Array
resp.audience_export_jobs[0].create_time #=> Time
resp.audience_export_jobs[0].update_time #=> Time
resp.audience_export_jobs[0].name #=> String
resp.audience_export_jobs[0].audience_generation_job_arn #=> String
resp.audience_export_jobs[0].audience_size.type #=> String, one of "ABSOLUTE", "PERCENTAGE"
resp.audience_export_jobs[0].audience_size.value #=> Integer
resp.audience_export_jobs[0].description #=> String
resp.audience_export_jobs[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE"
resp.audience_export_jobs[0].status_details.status_code #=> String
resp.audience_export_jobs[0].status_details.message #=> String
resp.audience_export_jobs[0].output_location #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :audience_generation_job_arn (String) —

    The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2680

def list_audience_export_jobs(params = {}, options = {})
  req = build_request(:list_audience_export_jobs, params)
  req.send_request(options)
end

#list_audience_generation_jobs(params = {}) ⇒ Types::ListAudienceGenerationJobsResponse

Returns a list of audience generation jobs.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_audience_generation_jobs({
  next_token: "NextToken",
  max_results: 1,
  configured_audience_model_arn: "ConfiguredAudienceModelArn",
  collaboration_id: "UUID",
})

Response structure


resp.next_token #=> String
resp.audience_generation_jobs #=> Array
resp.audience_generation_jobs[0].create_time #=> Time
resp.audience_generation_jobs[0].update_time #=> Time
resp.audience_generation_jobs[0].audience_generation_job_arn #=> String
resp.audience_generation_jobs[0].name #=> String
resp.audience_generation_jobs[0].description #=> String
resp.audience_generation_jobs[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED"
resp.audience_generation_jobs[0].configured_audience_model_arn #=> String
resp.audience_generation_jobs[0].collaboration_id #=> String
resp.audience_generation_jobs[0].started_by #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :configured_audience_model_arn (String) —

    The Amazon Resource Name (ARN) of the configured audience model that was used for the audience generation jobs that you are interested in.

  • :collaboration_id (String) —

    The identifier of the collaboration that contains the audience generation jobs that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2736

def list_audience_generation_jobs(params = {}, options = {})
  req = build_request(:list_audience_generation_jobs, params)
  req.send_request(options)
end

#list_audience_models(params = {}) ⇒ Types::ListAudienceModelsResponse

Returns a list of audience models.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_audience_models({
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.next_token #=> String
resp.audience_models #=> Array
resp.audience_models[0].create_time #=> Time
resp.audience_models[0].update_time #=> Time
resp.audience_models[0].audience_model_arn #=> String
resp.audience_models[0].name #=> String
resp.audience_models[0].training_dataset_arn #=> String
resp.audience_models[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED"
resp.audience_models[0].description #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2780

def list_audience_models(params = {}, options = {})
  req = build_request(:list_audience_models, params)
  req.send_request(options)
end

#list_collaboration_configured_model_algorithm_associations(params = {}) ⇒ Types::ListCollaborationConfiguredModelAlgorithmAssociationsResponse

Returns a list of the configured model algorithm associations in a collaboration.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_collaboration_configured_model_algorithm_associations({
  next_token: "NextToken",
  max_results: 1,
  collaboration_identifier: "UUID", # required
})

Response structure


resp.next_token #=> String
resp.collaboration_configured_model_algorithm_associations #=> Array
resp.collaboration_configured_model_algorithm_associations[0].create_time #=> Time
resp.collaboration_configured_model_algorithm_associations[0].update_time #=> Time
resp.collaboration_configured_model_algorithm_associations[0].configured_model_algorithm_association_arn #=> String
resp.collaboration_configured_model_algorithm_associations[0].name #=> String
resp.collaboration_configured_model_algorithm_associations[0].description #=> String
resp.collaboration_configured_model_algorithm_associations[0].membership_identifier #=> String
resp.collaboration_configured_model_algorithm_associations[0].collaboration_identifier #=> String
resp.collaboration_configured_model_algorithm_associations[0].configured_model_algorithm_arn #=> String
resp.collaboration_configured_model_algorithm_associations[0]. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :collaboration_identifier (required, String) —

    The collaboration ID of the collaboration that contains the configured model algorithm associations that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2832

def list_collaboration_configured_model_algorithm_associations(params = {}, options = {})
  req = build_request(:list_collaboration_configured_model_algorithm_associations, params)
  req.send_request(options)
end

#list_collaboration_ml_input_channels(params = {}) ⇒ Types::ListCollaborationMLInputChannelsResponse

Returns a list of the ML input channels in a collaboration.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_collaboration_ml_input_channels({
  next_token: "NextToken",
  max_results: 1,
  collaboration_identifier: "UUID", # required
})

Response structure


resp.next_token #=> String
resp.collaboration_ml_input_channels_list #=> Array
resp.collaboration_ml_input_channels_list[0].create_time #=> Time
resp.collaboration_ml_input_channels_list[0].update_time #=> Time
resp.collaboration_ml_input_channels_list[0].membership_identifier #=> String
resp.collaboration_ml_input_channels_list[0].collaboration_identifier #=> String
resp.collaboration_ml_input_channels_list[0].name #=> String
resp.collaboration_ml_input_channels_list[0].configured_model_algorithm_associations #=> Array
resp.collaboration_ml_input_channels_list[0].configured_model_algorithm_associations[0] #=> String
resp.collaboration_ml_input_channels_list[0].ml_input_channel_arn #=> String
resp.collaboration_ml_input_channels_list[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE"
resp.collaboration_ml_input_channels_list[0]. #=> String
resp.collaboration_ml_input_channels_list[0].description #=> String
resp.collaboration_ml_input_channels_list[0].payer_configuration. #=> String
resp.collaboration_ml_input_channels_list[0].payer_configuration. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum number of results to return.

  • :collaboration_identifier (required, String) —

    The collaboration ID of the collaboration that contains the ML input channels that you want to list.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2887

def list_collaboration_ml_input_channels(params = {}, options = {})
  req = build_request(:list_collaboration_ml_input_channels, params)
  req.send_request(options)
end

#list_collaboration_trained_model_export_jobs(params = {}) ⇒ Types::ListCollaborationTrainedModelExportJobsResponse

Returns a list of the export jobs for a trained model in a collaboration.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_collaboration_trained_model_export_jobs({
  next_token: "NextToken",
  max_results: 1,
  collaboration_identifier: "UUID", # required
  trained_model_arn: "TrainedModelArn", # required
  trained_model_version_identifier: "UUID",
})

Response structure


resp.next_token #=> String
resp.collaboration_trained_model_export_jobs #=> Array
resp.collaboration_trained_model_export_jobs[0].create_time #=> Time
resp.collaboration_trained_model_export_jobs[0].update_time #=> Time
resp.collaboration_trained_model_export_jobs[0].name #=> String
resp.collaboration_trained_model_export_jobs[0].output_configuration.members #=> Array
resp.collaboration_trained_model_export_jobs[0].output_configuration.members[0]. #=> String
resp.collaboration_trained_model_export_jobs[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE"
resp.collaboration_trained_model_export_jobs[0].status_details.status_code #=> String
resp.collaboration_trained_model_export_jobs[0].status_details.message #=> String
resp.collaboration_trained_model_export_jobs[0].description #=> String
resp.collaboration_trained_model_export_jobs[0]. #=> String
resp.collaboration_trained_model_export_jobs[0].trained_model_arn #=> String
resp.collaboration_trained_model_export_jobs[0].trained_model_version_identifier #=> String
resp.collaboration_trained_model_export_jobs[0].membership_identifier #=> String
resp.collaboration_trained_model_export_jobs[0].collaboration_identifier #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :collaboration_identifier (required, String) —

    The collaboration ID of the collaboration that contains the trained model export jobs that you are interested in.

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model that was used to create the export jobs that you are interested in.

  • :trained_model_version_identifier (String) —

    The version identifier of the trained model to filter export jobs by. When specified, only export jobs for this specific version of the trained model are returned.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 2955

def list_collaboration_trained_model_export_jobs(params = {}, options = {})
  req = build_request(:list_collaboration_trained_model_export_jobs, params)
  req.send_request(options)
end

#list_collaboration_trained_model_inference_jobs(params = {}) ⇒ Types::ListCollaborationTrainedModelInferenceJobsResponse

Returns a list of trained model inference jobs in a specified collaboration.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_collaboration_trained_model_inference_jobs({
  next_token: "NextToken",
  max_results: 1,
  collaboration_identifier: "UUID", # required
  trained_model_arn: "TrainedModelArn",
  trained_model_version_identifier: "UUID",
})

Response structure


resp.next_token #=> String
resp.collaboration_trained_model_inference_jobs #=> Array
resp.collaboration_trained_model_inference_jobs[0].trained_model_inference_job_arn #=> String
resp.collaboration_trained_model_inference_jobs[0].configured_model_algorithm_association_arn #=> String
resp.collaboration_trained_model_inference_jobs[0].membership_identifier #=> String
resp.collaboration_trained_model_inference_jobs[0].trained_model_arn #=> String
resp.collaboration_trained_model_inference_jobs[0].trained_model_version_identifier #=> String
resp.collaboration_trained_model_inference_jobs[0].collaboration_identifier #=> String
resp.collaboration_trained_model_inference_jobs[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED", "INACTIVE"
resp.collaboration_trained_model_inference_jobs[0].output_configuration.accept #=> String
resp.collaboration_trained_model_inference_jobs[0].output_configuration.members #=> Array
resp.collaboration_trained_model_inference_jobs[0].output_configuration.members[0]. #=> String
resp.collaboration_trained_model_inference_jobs[0].name #=> String
resp.collaboration_trained_model_inference_jobs[0].description #=> String
resp.collaboration_trained_model_inference_jobs[0].metrics_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.collaboration_trained_model_inference_jobs[0].metrics_status_details #=> String
resp.collaboration_trained_model_inference_jobs[0].logs_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.collaboration_trained_model_inference_jobs[0].logs_status_details #=> String
resp.collaboration_trained_model_inference_jobs[0]. #=> String
resp.collaboration_trained_model_inference_jobs[0].create_time #=> Time
resp.collaboration_trained_model_inference_jobs[0].update_time #=> Time
resp.collaboration_trained_model_inference_jobs[0]. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :collaboration_identifier (required, String) —

    The collaboration ID of the collaboration that contains the trained model inference jobs that you are interested in.

  • :trained_model_arn (String) —

    The Amazon Resource Name (ARN) of the trained model that was used to create the trained model inference jobs that you are interested in.

  • :trained_model_version_identifier (String) —

    The version identifier of the trained model to filter inference jobs by. When specified, only inference jobs that used this specific version of the trained model are returned.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3029

def list_collaboration_trained_model_inference_jobs(params = {}, options = {})
  req = build_request(:list_collaboration_trained_model_inference_jobs, params)
  req.send_request(options)
end

#list_collaboration_trained_models(params = {}) ⇒ Types::ListCollaborationTrainedModelsResponse

Returns a list of the trained models in a collaboration.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_collaboration_trained_models({
  next_token: "NextToken",
  max_results: 1,
  collaboration_identifier: "UUID", # required
})

Response structure


resp.next_token #=> String
resp.collaboration_trained_models #=> Array
resp.collaboration_trained_models[0].create_time #=> Time
resp.collaboration_trained_models[0].update_time #=> Time
resp.collaboration_trained_models[0].trained_model_arn #=> String
resp.collaboration_trained_models[0].name #=> String
resp.collaboration_trained_models[0].version_identifier #=> String
resp.collaboration_trained_models[0].incremental_training_data_channels #=> Array
resp.collaboration_trained_models[0].incremental_training_data_channels[0].channel_name #=> String
resp.collaboration_trained_models[0].incremental_training_data_channels[0].version_identifier #=> String
resp.collaboration_trained_models[0].incremental_training_data_channels[0].model_name #=> String
resp.collaboration_trained_models[0].description #=> String
resp.collaboration_trained_models[0].membership_identifier #=> String
resp.collaboration_trained_models[0].collaboration_identifier #=> String
resp.collaboration_trained_models[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED"
resp.collaboration_trained_models[0].configured_model_algorithm_association_arn #=> String
resp.collaboration_trained_models[0]. #=> String
resp.collaboration_trained_models[0]. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :collaboration_identifier (required, String) —

    The collaboration ID of the collaboration that contains the trained models you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3087

def list_collaboration_trained_models(params = {}, options = {})
  req = build_request(:list_collaboration_trained_models, params)
  req.send_request(options)
end

#list_configured_audience_models(params = {}) ⇒ Types::ListConfiguredAudienceModelsResponse

Returns a list of the configured audience models.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_configured_audience_models({
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.next_token #=> String
resp.configured_audience_models #=> Array
resp.configured_audience_models[0].create_time #=> Time
resp.configured_audience_models[0].update_time #=> Time
resp.configured_audience_models[0].name #=> String
resp.configured_audience_models[0].audience_model_arn #=> String
resp.configured_audience_models[0].output_config.destination.s3_destination.s3_uri #=> String
resp.configured_audience_models[0].output_config.role_arn #=> String
resp.configured_audience_models[0].description #=> String
resp.configured_audience_models[0].configured_audience_model_arn #=> String
resp.configured_audience_models[0].status #=> String, one of "ACTIVE"

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3133

def list_configured_audience_models(params = {}, options = {})
  req = build_request(:list_configured_audience_models, params)
  req.send_request(options)
end

#list_configured_model_algorithm_associations(params = {}) ⇒ Types::ListConfiguredModelAlgorithmAssociationsResponse

Returns a list of configured model algorithm associations.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_configured_model_algorithm_associations({
  next_token: "NextToken",
  max_results: 1,
  membership_identifier: "UUID", # required
})

Response structure


resp.next_token #=> String
resp.configured_model_algorithm_associations #=> Array
resp.configured_model_algorithm_associations[0].create_time #=> Time
resp.configured_model_algorithm_associations[0].update_time #=> Time
resp.configured_model_algorithm_associations[0].configured_model_algorithm_association_arn #=> String
resp.configured_model_algorithm_associations[0].configured_model_algorithm_arn #=> String
resp.configured_model_algorithm_associations[0].name #=> String
resp.configured_model_algorithm_associations[0].description #=> String
resp.configured_model_algorithm_associations[0].membership_identifier #=> String
resp.configured_model_algorithm_associations[0].collaboration_identifier #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :membership_identifier (required, String) —

    The membership ID of the member that created the configured model algorithm associations you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3183

def list_configured_model_algorithm_associations(params = {}, options = {})
  req = build_request(:list_configured_model_algorithm_associations, params)
  req.send_request(options)
end

#list_configured_model_algorithms(params = {}) ⇒ Types::ListConfiguredModelAlgorithmsResponse

Returns a list of configured model algorithms.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_configured_model_algorithms({
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.next_token #=> String
resp.configured_model_algorithms #=> Array
resp.configured_model_algorithms[0].create_time #=> Time
resp.configured_model_algorithms[0].update_time #=> Time
resp.configured_model_algorithms[0].configured_model_algorithm_arn #=> String
resp.configured_model_algorithms[0].name #=> String
resp.configured_model_algorithms[0].description #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3225

def list_configured_model_algorithms(params = {}, options = {})
  req = build_request(:list_configured_model_algorithms, params)
  req.send_request(options)
end

#list_ml_input_channels(params = {}) ⇒ Types::ListMLInputChannelsResponse

Returns a list of ML input channels.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_ml_input_channels({
  next_token: "NextToken",
  max_results: 1,
  membership_identifier: "UUID", # required
})

Response structure


resp.next_token #=> String
resp.ml_input_channels_list #=> Array
resp.ml_input_channels_list[0].create_time #=> Time
resp.ml_input_channels_list[0].update_time #=> Time
resp.ml_input_channels_list[0].membership_identifier #=> String
resp.ml_input_channels_list[0].collaboration_identifier #=> String
resp.ml_input_channels_list[0].name #=> String
resp.ml_input_channels_list[0].configured_model_algorithm_associations #=> Array
resp.ml_input_channels_list[0].configured_model_algorithm_associations[0] #=> String
resp.ml_input_channels_list[0].protected_query_identifier #=> String
resp.ml_input_channels_list[0].ml_input_channel_arn #=> String
resp.ml_input_channels_list[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE"
resp.ml_input_channels_list[0].description #=> String
resp.ml_input_channels_list[0].payer_configuration. #=> String
resp.ml_input_channels_list[0].payer_configuration. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum number of ML input channels to return.

  • :membership_identifier (required, String) —

    The membership ID of the membership that contains the ML input channels that you want to list.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3280

def list_ml_input_channels(params = {}, options = {})
  req = build_request(:list_ml_input_channels, params)
  req.send_request(options)
end

#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse

Returns a list of tags for a provided resource.

Examples:

Request syntax with placeholder values


resp = client.list_tags_for_resource({
  resource_arn: "TaggableArn", # required
})

Response structure


resp.tags #=> Hash
resp.tags["TagKey"] #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource that you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3310

def list_tags_for_resource(params = {}, options = {})
  req = build_request(:list_tags_for_resource, params)
  req.send_request(options)
end

#list_trained_model_inference_jobs(params = {}) ⇒ Types::ListTrainedModelInferenceJobsResponse

Returns a list of trained model inference jobs that match the request parameters.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_trained_model_inference_jobs({
  next_token: "NextToken",
  max_results: 1,
  membership_identifier: "UUID", # required
  trained_model_arn: "TrainedModelArn",
  trained_model_version_identifier: "UUID",
})

Response structure


resp.next_token #=> String
resp.trained_model_inference_jobs #=> Array
resp.trained_model_inference_jobs[0].trained_model_inference_job_arn #=> String
resp.trained_model_inference_jobs[0].configured_model_algorithm_association_arn #=> String
resp.trained_model_inference_jobs[0].membership_identifier #=> String
resp.trained_model_inference_jobs[0].trained_model_arn #=> String
resp.trained_model_inference_jobs[0].trained_model_version_identifier #=> String
resp.trained_model_inference_jobs[0].collaboration_identifier #=> String
resp.trained_model_inference_jobs[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED", "INACTIVE"
resp.trained_model_inference_jobs[0].output_configuration.accept #=> String
resp.trained_model_inference_jobs[0].output_configuration.members #=> Array
resp.trained_model_inference_jobs[0].output_configuration.members[0]. #=> String
resp.trained_model_inference_jobs[0].name #=> String
resp.trained_model_inference_jobs[0].description #=> String
resp.trained_model_inference_jobs[0].metrics_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.trained_model_inference_jobs[0].metrics_status_details #=> String
resp.trained_model_inference_jobs[0].logs_status #=> String, one of "PUBLISH_SUCCEEDED", "PUBLISH_FAILED"
resp.trained_model_inference_jobs[0].logs_status_details #=> String
resp.trained_model_inference_jobs[0]. #=> String
resp.trained_model_inference_jobs[0].create_time #=> Time
resp.trained_model_inference_jobs[0].update_time #=> Time

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :membership_identifier (required, String) —

    The membership

  • :trained_model_arn (String) —

    The Amazon Resource Name (ARN) of a trained model that was used to create the trained model inference jobs that you are interested in.

  • :trained_model_version_identifier (String) —

    The version identifier of the trained model to filter inference jobs by. When specified, only inference jobs that used this specific version of the trained model are returned.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3382

def list_trained_model_inference_jobs(params = {}, options = {})
  req = build_request(:list_trained_model_inference_jobs, params)
  req.send_request(options)
end

#list_trained_model_versions(params = {}) ⇒ Types::ListTrainedModelVersionsResponse

Returns a list of trained model versions for a specified trained model. This operation allows you to view all versions of a trained model, including information about their status and creation details. You can use this to track the evolution of your trained models and select specific versions for inference or further training.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_trained_model_versions({
  next_token: "NextToken",
  max_results: 1,
  membership_identifier: "UUID", # required
  trained_model_arn: "TrainedModelArn", # required
  status: "CREATE_PENDING", # accepts CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED, ACTIVE, DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED, INACTIVE, CANCEL_PENDING, CANCEL_IN_PROGRESS, CANCEL_FAILED
})

Response structure


resp.next_token #=> String
resp.trained_models #=> Array
resp.trained_models[0].create_time #=> Time
resp.trained_models[0].update_time #=> Time
resp.trained_models[0].trained_model_arn #=> String
resp.trained_models[0].version_identifier #=> String
resp.trained_models[0].incremental_training_data_channels #=> Array
resp.trained_models[0].incremental_training_data_channels[0].channel_name #=> String
resp.trained_models[0].incremental_training_data_channels[0].version_identifier #=> String
resp.trained_models[0].incremental_training_data_channels[0].model_name #=> String
resp.trained_models[0].name #=> String
resp.trained_models[0].description #=> String
resp.trained_models[0].membership_identifier #=> String
resp.trained_models[0].collaboration_identifier #=> String
resp.trained_models[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED"
resp.trained_models[0].configured_model_algorithm_association_arn #=> String
resp.trained_models[0]. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The pagination token from a previous ‘ListTrainedModelVersions` request. Use this token to retrieve the next page of results.

  • :max_results (Integer) —

    The maximum number of trained model versions to return in a single page. The default value is 10, and the maximum value is 100.

  • :membership_identifier (required, String) —

    The membership identifier for the collaboration that contains the trained model.

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model for which to list versions.

  • :status (String) —

    Filter the results to only include trained model versions with the specified status. Valid values include ‘CREATE_PENDING`, `CREATE_IN_PROGRESS`, `ACTIVE`, `CREATE_FAILED`, and others.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3455

def list_trained_model_versions(params = {}, options = {})
  req = build_request(:list_trained_model_versions, params)
  req.send_request(options)
end

#list_trained_models(params = {}) ⇒ Types::ListTrainedModelsResponse

Returns a list of trained models.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_trained_models({
  next_token: "NextToken",
  max_results: 1,
  membership_identifier: "UUID", # required
})

Response structure


resp.next_token #=> String
resp.trained_models #=> Array
resp.trained_models[0].create_time #=> Time
resp.trained_models[0].update_time #=> Time
resp.trained_models[0].trained_model_arn #=> String
resp.trained_models[0].version_identifier #=> String
resp.trained_models[0].incremental_training_data_channels #=> Array
resp.trained_models[0].incremental_training_data_channels[0].channel_name #=> String
resp.trained_models[0].incremental_training_data_channels[0].version_identifier #=> String
resp.trained_models[0].incremental_training_data_channels[0].model_name #=> String
resp.trained_models[0].name #=> String
resp.trained_models[0].description #=> String
resp.trained_models[0].membership_identifier #=> String
resp.trained_models[0].collaboration_identifier #=> String
resp.trained_models[0].status #=> String, one of "CREATE_PENDING", "CREATE_IN_PROGRESS", "CREATE_FAILED", "ACTIVE", "DELETE_PENDING", "DELETE_IN_PROGRESS", "DELETE_FAILED", "INACTIVE", "CANCEL_PENDING", "CANCEL_IN_PROGRESS", "CANCEL_FAILED"
resp.trained_models[0].configured_model_algorithm_association_arn #=> String
resp.trained_models[0]. #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

  • :membership_identifier (required, String) —

    The membership ID of the member that created the trained models you are interested in.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3512

def list_trained_models(params = {}, options = {})
  req = build_request(:list_trained_models, params)
  req.send_request(options)
end

#list_training_datasets(params = {}) ⇒ Types::ListTrainingDatasetsResponse

Returns a list of training datasets.

The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.

Examples:

Request syntax with placeholder values


resp = client.list_training_datasets({
  next_token: "NextToken",
  max_results: 1,
})

Response structure


resp.next_token #=> String
resp.training_datasets #=> Array
resp.training_datasets[0].create_time #=> Time
resp.training_datasets[0].update_time #=> Time
resp.training_datasets[0].training_dataset_arn #=> String
resp.training_datasets[0].name #=> String
resp.training_datasets[0].status #=> String, one of "ACTIVE"
resp.training_datasets[0].description #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :next_token (String) —

    The token value retrieved from a previous call to access the next page of results.

  • :max_results (Integer) —

    The maximum size of the results that is returned per call.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3555

def list_training_datasets(params = {}, options = {})
  req = build_request(:list_training_datasets, params)
  req.send_request(options)
end

#put_configured_audience_model_policy(params = {}) ⇒ Types::PutConfiguredAudienceModelPolicyResponse

Create or update the resource policy for a configured audience model.

Examples:

Request syntax with placeholder values


resp = client.put_configured_audience_model_policy({
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
  configured_audience_model_policy: "ResourcePolicy", # required
  previous_policy_hash: "Hash",
  policy_existence_condition: "POLICY_MUST_EXIST", # accepts POLICY_MUST_EXIST, POLICY_MUST_NOT_EXIST
})

Response structure


resp.configured_audience_model_policy #=> String
resp.policy_hash #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured audience model that the resource policy will govern.

  • :configured_audience_model_policy (required, String) —

    The IAM resource policy.

  • :previous_policy_hash (String) —

    A cryptographic hash of the contents of the policy used to prevent unexpected concurrent modification of the policy.

  • :policy_existence_condition (String) —

    Use this to prevent unexpected concurrent modification of the policy.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3599

def put_configured_audience_model_policy(params = {}, options = {})
  req = build_request(:put_configured_audience_model_policy, params)
  req.send_request(options)
end

#put_ml_configuration(params = {}) ⇒ Struct

Assigns information about an ML configuration.

Examples:

Request syntax with placeholder values


resp = client.put_ml_configuration({
  membership_identifier: "UUID", # required
  default_output_location: { # required
    destination: {
      s3_destination: { # required
        s3_uri: "S3Path", # required
      },
    },
    role_arn: "IamRoleArn", # required
  },
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the member that is being configured.

  • :default_output_location (required, Types::MLOutputConfiguration) —

    The default Amazon S3 location where ML output is stored for the specified member.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3633

def put_ml_configuration(params = {}, options = {})
  req = build_request(:put_ml_configuration, params)
  req.send_request(options)
end

#start_audience_export_job(params = {}) ⇒ Struct

Export an audience of a specified size after you have generated an audience.

Examples:

Request syntax with placeholder values


resp = client.start_audience_export_job({
  name: "NameString", # required
  audience_generation_job_arn: "AudienceGenerationJobArn", # required
  audience_size: { # required
    type: "ABSOLUTE", # required, accepts ABSOLUTE, PERCENTAGE
    value: 1, # required
  },
  description: "ResourceDescription",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name of the audience export job.

  • :audience_generation_job_arn (required, String) —

    The Amazon Resource Name (ARN) of the audience generation job that you want to export.

  • :audience_size (required, Types::AudienceSize) —

    The size of the generated audience. Must match one of the sizes in the configured audience model.

  • :description (String) —

    The description of the audience export job.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3673

def start_audience_export_job(params = {}, options = {})
  req = build_request(:start_audience_export_job, params)
  req.send_request(options)
end

#start_audience_generation_job(params = {}) ⇒ Types::StartAudienceGenerationJobResponse

Information necessary to start the audience generation job.

Examples:

Request syntax with placeholder values


resp = client.start_audience_generation_job({
  name: "NameString", # required
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
  seed_audience: { # required
    data_source: {
      s3_uri: "S3Path", # required
    },
    role_arn: "IamRoleArn", # required
    sql_parameters: {
      query_string: "ProtectedQuerySQLParametersQueryStringString",
      analysis_template_arn: "AnalysisTemplateArn",
      parameters: {
        "ParameterName" => "ParameterValue",
      },
    },
    sql_compute_configuration: {
      worker: {
        type: "CR.1X", # accepts CR.1X, CR.4X
        number: 1,
        properties: {
          spark: {
            "SparkPropertyKey" => "SparkPropertyValue",
          },
        },
      },
    },
  },
  include_seed_in_output: false,
  collaboration_id: "UUID",
  description: "ResourceDescription",
  tags: {
    "TagKey" => "TagValue",
  },
})

Response structure


resp.audience_generation_job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name of the audience generation job.

  • :configured_audience_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the configured audience model that is used for this audience generation job.

  • :seed_audience (required, Types::AudienceGenerationJobDataSource) —

    The seed audience that is used to generate the audience.

  • :include_seed_in_output (Boolean) —

    Whether the seed audience is included in the audience generation output.

  • :collaboration_id (String) —

    The identifier of the collaboration that contains the audience generation job.

  • :description (String) —

    The description of the audience generation job.

  • :tags (Hash<String,String>) —

    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.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3782

def start_audience_generation_job(params = {}, options = {})
  req = build_request(:start_audience_generation_job, params)
  req.send_request(options)
end

#start_trained_model_export_job(params = {}) ⇒ Struct

Provides the information necessary to start a trained model export job.

Examples:

Request syntax with placeholder values


resp = client.start_trained_model_export_job({
  name: "NameString", # required
  trained_model_arn: "TrainedModelArn", # required
  trained_model_version_identifier: "UUID",
  membership_identifier: "UUID", # required
  output_configuration: { # required
    members: [ # required
      {
        account_id: "AccountId", # required
      },
    ],
  },
  description: "ResourceDescription",
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :name (required, String) —

    The name of the trained model export job.

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model that you want to export.

  • :trained_model_version_identifier (String) —

    The version identifier of the trained model to export. This specifies which version of the trained model should be exported to the specified destination.

  • :membership_identifier (required, String) —

    The membership ID of the member that is receiving the exported trained model artifacts.

  • :output_configuration (required, Types::TrainedModelExportOutputConfiguration) —

    The output configuration information for the trained model export job.

  • :description (String) —

    The description of the trained model export job.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3835

def start_trained_model_export_job(params = {}, options = {})
  req = build_request(:start_trained_model_export_job, params)
  req.send_request(options)
end

#start_trained_model_inference_job(params = {}) ⇒ Types::StartTrainedModelInferenceJobResponse

Defines the information necessary to begin a trained model inference job.

Examples:

Request syntax with placeholder values


resp = client.start_trained_model_inference_job({
  membership_identifier: "UUID", # required
  name: "NameString", # required
  trained_model_arn: "TrainedModelArn", # required
  trained_model_version_identifier: "UUID",
  configured_model_algorithm_association_arn: "ConfiguredModelAlgorithmAssociationArn",
  resource_config: { # required
    instance_type: "ml.r7i.48xlarge", # required, accepts ml.r7i.48xlarge, ml.r6i.16xlarge, ml.m6i.xlarge, ml.m5.4xlarge, ml.p2.xlarge, ml.m4.16xlarge, ml.r7i.16xlarge, ml.m7i.xlarge, ml.m6i.12xlarge, ml.r7i.8xlarge, ml.r7i.large, ml.m7i.12xlarge, ml.m6i.24xlarge, ml.m7i.24xlarge, ml.r6i.8xlarge, ml.r6i.large, ml.g5.2xlarge, ml.m5.large, ml.m7i.48xlarge, ml.m6i.16xlarge, ml.p2.16xlarge, ml.g5.4xlarge, ml.m7i.16xlarge, ml.c4.2xlarge, ml.c5.2xlarge, ml.c6i.32xlarge, ml.c4.4xlarge, ml.g5.8xlarge, ml.c6i.xlarge, ml.c5.4xlarge, ml.g4dn.xlarge, ml.c7i.xlarge, ml.c6i.12xlarge, ml.g4dn.12xlarge, ml.c7i.12xlarge, ml.c6i.24xlarge, ml.g4dn.2xlarge, ml.c7i.24xlarge, ml.c7i.2xlarge, ml.c4.8xlarge, ml.c6i.2xlarge, ml.g4dn.4xlarge, ml.c7i.48xlarge, ml.c7i.4xlarge, ml.c6i.16xlarge, ml.c5.9xlarge, ml.g4dn.16xlarge, ml.c7i.16xlarge, ml.c6i.4xlarge, ml.c5.xlarge, ml.c4.xlarge, ml.g4dn.8xlarge, ml.c7i.8xlarge, ml.c7i.large, ml.g5.xlarge, ml.c6i.8xlarge, ml.c6i.large, ml.g5.12xlarge, ml.g5.24xlarge, ml.m7i.2xlarge, ml.c5.18xlarge, ml.g5.48xlarge, ml.m6i.2xlarge, ml.g5.16xlarge, ml.m7i.4xlarge, ml.r6i.32xlarge, ml.m6i.4xlarge, ml.m5.xlarge, ml.m4.10xlarge, ml.r6i.xlarge, ml.m5.12xlarge, ml.m4.xlarge, ml.r7i.2xlarge, ml.r7i.xlarge, ml.r6i.12xlarge, ml.m5.24xlarge, ml.r7i.12xlarge, ml.m7i.8xlarge, ml.m7i.large, ml.r6i.24xlarge, ml.r6i.2xlarge, ml.m4.2xlarge, ml.r7i.24xlarge, ml.r7i.4xlarge, ml.m6i.8xlarge, ml.m6i.large, ml.m5.2xlarge, ml.p2.8xlarge, ml.r6i.4xlarge, ml.m6i.32xlarge, ml.m4.4xlarge, ml.p3.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge
    instance_count: 1,
  },
  output_configuration: { # required
    accept: "InferenceOutputConfigurationAcceptString",
    members: [ # required
      {
        account_id: "AccountId", # required
      },
    ],
  },
  data_source: { # required
    ml_input_channel_arn: "MLInputChannelArn", # required
  },
  description: "ResourceDescription",
  container_execution_parameters: {
    max_payload_in_mb: 1,
  },
  environment: {
    "InferenceEnvironmentMapKeyString" => "InferenceEnvironmentMapValueString",
  },
  kms_key_arn: "KmsKeyArn",
  tags: {
    "TagKey" => "TagValue",
  },
  ml_model_inference_payer_account_id: "AccountId",
})

Response structure


resp.trained_model_inference_job_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :membership_identifier (required, String) —

    The membership ID of the membership that contains the trained model inference job.

  • :name (required, String) —

    The name of the trained model inference job.

  • :trained_model_arn (required, String) —

    The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.

  • :trained_model_version_identifier (String) —

    The version identifier of the trained model to use for inference. This specifies which version of the trained model should be used to generate predictions on the input data.

  • :configured_model_algorithm_association_arn (String) —

    The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.

  • :resource_config (required, Types::InferenceResourceConfig) —

    Defines the resource configuration for the trained model inference job.

  • :output_configuration (required, Types::InferenceOutputConfiguration) —

    Defines the output configuration information for the trained model inference job.

  • :data_source (required, Types::ModelInferenceDataSource) —

    Defines the data source that is used for the trained model inference job.

  • :description (String) —

    The description of the trained model inference job.

  • :container_execution_parameters (Types::InferenceContainerExecutionParameters) —

    The execution parameters for the container.

  • :environment (Hash<String,String>) —

    The environment variables to set in the Docker container.

  • :kms_key_arn (String) —

    The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

  • :tags (Hash<String,String>) —

    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.

  • :ml_model_inference_payer_account_id (String) —

    The account ID of the member that is responsible for paying for model inference costs.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 3974

def start_trained_model_inference_job(params = {}, options = {})
  req = build_request(:start_trained_model_inference_job, params)
  req.send_request(options)
end

#tag_resource(params = {}) ⇒ Struct

Adds metadata tags to a specified resource.

Examples:

Request syntax with placeholder values


resp = client.tag_resource({
  resource_arn: "TaggableArn", # required
  tags: { # required
    "TagKey" => "TagValue",
  },
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource that you want to assign tags.

  • :tags (required, Hash<String,String>) —

    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 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.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4032

def tag_resource(params = {}, options = {})
  req = build_request(:tag_resource, params)
  req.send_request(options)
end

#untag_resource(params = {}) ⇒ Struct

Removes metadata tags from a specified resource.

Examples:

Request syntax with placeholder values


resp = client.untag_resource({
  resource_arn: "TaggableArn", # required
  tag_keys: ["TagKey"], # required
})

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :resource_arn (required, String) —

    The Amazon Resource Name (ARN) of the resource that you want to remove tags from.

  • :tag_keys (required, Array<String>) —

    The key values of tags that you want to remove.

Returns:

  • (Struct) —

    Returns an empty response.

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4059

def untag_resource(params = {}, options = {})
  req = build_request(:untag_resource, params)
  req.send_request(options)
end

#update_configured_audience_model(params = {}) ⇒ Types::UpdateConfiguredAudienceModelResponse

Provides the information necessary to update a configured audience model. Updates that impact audience generation jobs take effect when a new job starts, but do not impact currently running jobs.

Examples:

Request syntax with placeholder values


resp = client.update_configured_audience_model({
  configured_audience_model_arn: "ConfiguredAudienceModelArn", # required
  output_config: {
    destination: { # required
      s3_destination: { # required
        s3_uri: "S3Path", # required
      },
    },
    role_arn: "IamRoleArn", # required
  },
  audience_model_arn: "AudienceModelArn",
  shared_audience_metrics: ["ALL"], # accepts ALL, NONE
  min_matching_seed_size: 1,
  audience_size_config: {
    audience_size_type: "ABSOLUTE", # required, accepts ABSOLUTE, PERCENTAGE
    audience_size_bins: [1], # required
  },
  description: "ResourceDescription",
})

Response structure


resp.configured_audience_model_arn #=> String

Parameters:

  • params (Hash) (defaults to: {}) —

    ({})

Options Hash (params):

  • :configured_audience_model_arn (required, String) —

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

  • :output_config (Types::ConfiguredAudienceModelOutputConfig) —

    The new output configuration.

  • :audience_model_arn (String) —

    The Amazon Resource Name (ARN) of the new audience model that you want to use.

  • :shared_audience_metrics (Array<String>) —

    The new value for whether to share audience metrics.

  • :min_matching_seed_size (Integer) —

    The minimum number of users from the seed audience that must match with users in the training data of the audience model.

  • :audience_size_config (Types::AudienceSizeConfig) —

    The new audience size configuration.

  • :description (String) —

    The new description of the configured audience model.

Returns:

See Also:



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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4126

def update_configured_audience_model(params = {}, options = {})
  req = build_request(:update_configured_audience_model, params)
  req.send_request(options)
end

#waiter_names ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Deprecated. 


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# File 'lib/aws-sdk-cleanroomsml/client.rb', line 4155

def waiter_names
  []
end