We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
*
* CreateAutoMLJobV2 can manage tabular problem types identical to those of
- * its previous version CreateAutoMLJob, as well as non-tabular problem types
- * such as image or text classification.
CreateAutoMLJob, as well as time-series forecasting,
+ * and non-tabular problem types such as image or text classification.
* Find guidelines about how to migrate a CreateAutoMLJob to
* CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
* CreateAutoMLJobV2 can manage tabular problem types identical to those of
- * its previous version CreateAutoMLJob, as well as non-tabular problem types
- * such as image or text classification.
CreateAutoMLJob, as well as time-series forecasting,
+ * and non-tabular problem types such as image or text classification.
* Find guidelines about how to migrate a CreateAutoMLJob to
* CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
Creates a definition for a job that monitors data quality and drift. For information - * about model monitor, see Amazon SageMaker Model Monitor.
+ * about model monitor, see Amazon SageMaker Model + * Monitor. * @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts b/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts index d50e1704bf20..b4de9792dcbe 100644 --- a/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts @@ -65,6 +65,12 @@ export interface CreateFeatureGroupCommandOutput extends CreateFeatureGroupRespo * { // FeatureDefinition * FeatureName: "STRING_VALUE", * FeatureType: "Integral" || "Fractional" || "String", + * CollectionType: "List" || "Set" || "Vector", + * CollectionConfig: { // CollectionConfig Union: only one key present + * VectorConfig: { // VectorConfig + * Dimension: Number("int"), // required + * }, + * }, * }, * ], * OnlineStoreConfig: { // OnlineStoreConfig @@ -76,6 +82,7 @@ export interface CreateFeatureGroupCommandOutput extends CreateFeatureGroupRespo * Unit: "Seconds" || "Minutes" || "Hours" || "Days" || "Weeks", * Value: Number("int"), * }, + * StorageType: "Standard" || "InMemory", * }, * OfflineStoreConfig: { // OfflineStoreConfig * S3StorageConfig: { // S3StorageConfig diff --git a/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts b/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts index 1586a6e5c774..96c34dd4e17e 100644 --- a/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts @@ -43,7 +43,8 @@ export interface CreateModelQualityJobDefinitionCommandOutput /** * @public *Creates a definition for a job that monitors model quality and drift. For information - * about model monitor, see Amazon SageMaker Model Monitor.
+ * about model monitor, see Amazon SageMaker Model + * Monitor. * @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts b/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts index c6bf568595a3..f5301b0c7c54 100644 --- a/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts @@ -37,8 +37,8 @@ export interface CreateMonitoringScheduleCommandOutput extends CreateMonitoringS /** * @public - *Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data - * captured for an Amazon SageMaker Endpoint.
+ *Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to + * monitor the data captured for an Amazon SageMaker Endpoint.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteDomainCommand.ts b/clients/client-sagemaker/src/commands/DeleteDomainCommand.ts index 0367e018858b..f592af17e88a 100644 --- a/clients/client-sagemaker/src/commands/DeleteDomainCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteDomainCommand.ts @@ -14,7 +14,7 @@ import { SMITHY_CONTEXT_KEY, } from "@smithy/types"; -import { DeleteDomainRequest } from "../models/models_1"; +import { DeleteDomainRequest } from "../models/models_2"; import { de_DeleteDomainCommand, se_DeleteDomainCommand } from "../protocols/Aws_json1_1"; import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient"; diff --git a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts index 7874e23f7418..caee32998bd1 100644 --- a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts @@ -14,7 +14,7 @@ import { SMITHY_CONTEXT_KEY, } from "@smithy/types"; -import { DeleteEdgeDeploymentPlanRequest } from "../models/models_1"; +import { DeleteEdgeDeploymentPlanRequest } from "../models/models_2"; import { de_DeleteEdgeDeploymentPlanCommand, se_DeleteEdgeDeploymentPlanCommand } from "../protocols/Aws_json1_1"; import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient"; diff --git a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts index 9a239ed1f66c..aa176e4288c7 100644 --- a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts @@ -14,7 +14,7 @@ import { SMITHY_CONTEXT_KEY, } from "@smithy/types"; -import { DeleteEdgeDeploymentStageRequest } from "../models/models_1"; +import { DeleteEdgeDeploymentStageRequest } from "../models/models_2"; import { de_DeleteEdgeDeploymentStageCommand, se_DeleteEdgeDeploymentStageCommand } from "../protocols/Aws_json1_1"; import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient"; diff --git a/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts b/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts index 9f69a0fa802c..241dc58aff25 100644 --- a/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts @@ -14,7 +14,7 @@ import { SMITHY_CONTEXT_KEY, } from "@smithy/types"; -import { DeleteEndpointInput } from "../models/models_1"; +import { DeleteEndpointInput } from "../models/models_2"; import { de_DeleteEndpointCommand, se_DeleteEndpointCommand } from "../protocols/Aws_json1_1"; import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient"; diff --git a/clients/client-sagemaker/src/commands/DescribeFeatureGroupCommand.ts b/clients/client-sagemaker/src/commands/DescribeFeatureGroupCommand.ts index 3e8de3e34390..3555bb16c29b 100644 --- a/clients/client-sagemaker/src/commands/DescribeFeatureGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeFeatureGroupCommand.ts @@ -61,6 +61,12 @@ export interface DescribeFeatureGroupCommandOutput extends DescribeFeatureGroupR * // { // FeatureDefinition * // FeatureName: "STRING_VALUE", * // FeatureType: "Integral" || "Fractional" || "String", + * // CollectionType: "List" || "Set" || "Vector", + * // CollectionConfig: { // CollectionConfig Union: only one key present + * // VectorConfig: { // VectorConfig + * // Dimension: Number("int"), // required + * // }, + * // }, * // }, * // ], * // CreationTime: new Date("TIMESTAMP"), // required @@ -74,6 +80,7 @@ export interface DescribeFeatureGroupCommandOutput extends DescribeFeatureGroupR * // Unit: "Seconds" || "Minutes" || "Hours" || "Days" || "Weeks", * // Value: Number("int"), * // }, + * // StorageType: "Standard" || "InMemory", * // }, * // OfflineStoreConfig: { // OfflineStoreConfig * // S3StorageConfig: { // S3StorageConfig diff --git a/clients/client-sagemaker/src/commands/SearchCommand.ts b/clients/client-sagemaker/src/commands/SearchCommand.ts index 97e0470f8b14..58b8ddcdadd3 100644 --- a/clients/client-sagemaker/src/commands/SearchCommand.ts +++ b/clients/client-sagemaker/src/commands/SearchCommand.ts @@ -1351,6 +1351,12 @@ export interface SearchCommandOutput extends SearchResponse, __MetadataBearer {} * // { // FeatureDefinition * // FeatureName: "STRING_VALUE", * // FeatureType: "Integral" || "Fractional" || "String", + * // CollectionType: "List" || "Set" || "Vector", + * // CollectionConfig: { // CollectionConfig Union: only one key present + * // VectorConfig: { // VectorConfig + * // Dimension: Number("int"), // required + * // }, + * // }, * // }, * // ], * // CreationTime: new Date("TIMESTAMP"), @@ -1364,6 +1370,7 @@ export interface SearchCommandOutput extends SearchResponse, __MetadataBearer {} * // Unit: "Seconds" || "Minutes" || "Hours" || "Days" || "Weeks", * // Value: Number("int"), * // }, + * // StorageType: "Standard" || "InMemory", * // }, * // OfflineStoreConfig: { // OfflineStoreConfig * // S3StorageConfig: { // S3StorageConfig diff --git a/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts b/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts index 9d3410b02787..ece2ae34f212 100644 --- a/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts @@ -61,6 +61,12 @@ export interface UpdateFeatureGroupCommandOutput extends UpdateFeatureGroupRespo * { // FeatureDefinition * FeatureName: "STRING_VALUE", * FeatureType: "Integral" || "Fractional" || "String", + * CollectionType: "List" || "Set" || "Vector", + * CollectionConfig: { // CollectionConfig Union: only one key present + * VectorConfig: { // VectorConfig + * Dimension: Number("int"), // required + * }, + * }, * }, * ], * OnlineStoreConfig: { // OnlineStoreConfigUpdate diff --git a/clients/client-sagemaker/src/models/models_0.ts b/clients/client-sagemaker/src/models/models_0.ts index 34255d14cc2d..db2e83b87726 100644 --- a/clients/client-sagemaker/src/models/models_0.ts +++ b/clients/client-sagemaker/src/models/models_0.ts @@ -5933,7 +5933,7 @@ export interface HolidayConfigAttributes { /** * @public *The country code for the holiday calendar.
- *For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your + *
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your * choice.
*/ CountryCode?: string; @@ -6157,7 +6157,7 @@ export interface TimeSeriesForecastingJobConfig { /** * @public - *The collection of holidays featurization attributes used to incorporate national holiday + *
The collection of holiday featurization attributes used to incorporate national holiday * information into your forecasting model.
*/ HolidayConfig?: HolidayConfigAttributes[]; @@ -6739,7 +6739,7 @@ export interface MonitoringCsvDatasetFormat { export interface MonitoringJsonDatasetFormat { /** * @public - *Indicates if the file should be read as a json object per line.
+ *Indicates if the file should be read as a JSON object per line.
*/ Line?: boolean; } @@ -7342,20 +7342,20 @@ export interface CanvasAppSettings { /** * @public *Configuration specifying how to treat different headers. If no headers are specified - * SageMaker will by default base64 encode when capturing the data.
+ * Amazon SageMaker will by default base64 encode when capturing the data. */ export interface CaptureContentTypeHeader { /** * @public - *The list of all content type headers that SageMaker will treat as CSV and capture - * accordingly.
+ *The list of all content type headers that Amazon SageMaker will treat as CSV and + * capture accordingly.
*/ CsvContentTypes?: string[]; /** * @public - *The list of all content type headers that SageMaker will treat as JSON and capture - * accordingly.
+ *The list of all content type headers that SageMaker will treat as JSON and + * capture accordingly.
*/ JsonContentTypes?: string[]; } @@ -8133,6 +8133,62 @@ export interface CognitoMemberDefinition { ClientId: string | undefined; } +/** + * @public + *Configuration for your vector collection type.
+ */ +export interface VectorConfig { + /** + * @public + *The number of elements in your vector.
+ */ + Dimension: number | undefined; +} + +/** + * @public + *Configuration for your collection.
+ */ +export type CollectionConfig = CollectionConfig.VectorConfigMember | CollectionConfig.$UnknownMember; + +/** + * @public + */ +export namespace CollectionConfig { + /** + * @public + *Configuration for your vector collection type.
+ *
+ * Dimension: The number of elements in your vector.
Configuration information for the Amazon SageMaker Debugger output tensor collections.
@@ -8154,6 +8210,21 @@ export interface CollectionConfiguration { CollectionParameters?: RecordAn Amazon S3 URI to a script that is called per row prior to running analysis. It can - * base64 decode the payload and convert it into a flatted json so that the built-in container - * can use the converted data. Applicable only for the built-in (first party) - * containers.
+ * base64 decode the payload and convert it into a flattened JSON so that the built-in container can use + * the converted data. Applicable only for the built-in (first party) containers. */ RecordPreprocessorSourceUri?: string; /** * @public - *An Amazon S3 URI to a script that is called after analysis has been performed. - * Applicable only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable + * only for the built-in (first party) containers.
*/ PostAnalyticsProcessorSourceUri?: string; @@ -10888,9 +10958,9 @@ export interface MonitoringStatisticsResource { /** * @public - *Configuration for monitoring constraints and monitoring statistics. These baseline - * resources are compared against the results of the current job from the series of jobs - * scheduled to collect data periodically.
+ *Configuration for monitoring constraints and monitoring statistics. These baseline resources are + * compared against the results of the current job from the series of jobs scheduled to collect data + * periodically.
*/ export interface DataQualityBaselineConfig { /** @@ -10941,8 +11011,8 @@ export interface EndpointInput { /** * @public - *Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key.
- * Defaults to FullyReplicated
+ *
Whether input data distributed in Amazon S3 is fully replicated or sharded by an
+ * Amazon S3 key. Defaults to FullyReplicated
*
A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a - * monitoring job.
+ *A URI that identifies the Amazon S3 storage location where Amazon SageMaker + * saves the results of a monitoring job.
*/ S3Uri: string | undefined; /** * @public - *The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a - * monitoring job. LocalPath is an absolute path for the output data.
+ *The local path to the Amazon S3 storage location where Amazon SageMaker + * saves the results of a monitoring job. LocalPath is an absolute path for the output + * data.
*/ LocalPath: string | undefined; @@ -11062,7 +11133,8 @@ export interface MonitoringS3Output { export interface MonitoringOutput { /** * @public - *The Amazon S3 storage location where the results of a monitoring job are saved.
+ *The Amazon S3 storage location where the results of a monitoring job are + * saved.
*/ S3Output: MonitoringS3Output | undefined; } @@ -11081,8 +11153,8 @@ export interface MonitoringOutputConfig { /** * @public - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker - * uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
+ *The Key Management Service (KMS) key that Amazon SageMaker uses to + * encrypt the model artifacts at rest using Amazon S3 server-side encryption.
*/ KmsKeyId?: string; } @@ -11170,9 +11242,9 @@ export interface MonitoringClusterConfig { /** * @public - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon - * SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) - * that run the model monitoring job.
+ *The Key Management Service (KMS) key that Amazon SageMaker uses to + * encrypt data on the storage volume attached to the ML compute instance(s) that run the + * model monitoring job.
*/ VolumeKmsKeyId?: string; } @@ -11286,8 +11358,8 @@ export interface CreateDataQualityJobDefinitionRequest { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to - * perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; @@ -11299,8 +11371,9 @@ export interface CreateDataQualityJobDefinitionRequest { /** * @public - *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost - * Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see + * + * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
*/ Tags?: Tag[]; } @@ -11438,87 +11511,3 @@ export interface CreateDeviceFleetRequest { */ EnableIotRoleAlias?: boolean; } - -/** - * @public - *The JupyterServer app settings.
- */ -export interface JupyterServerAppSettings { - /** - * @public - *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
- */ - CodeRepositories?: CodeRepository[]; -} - -/** - * @public - *A custom SageMaker image. For more information, see - * Bring your own SageMaker image.
- */ -export interface CustomImage { - /** - * @public - *The name of the CustomImage. Must be unique to your account.
- */ - ImageName: string | undefined; - - /** - * @public - *The version number of the CustomImage.
- */ - ImageVersionNumber?: number; - - /** - * @public - *The name of the AppImageConfig.
- */ - AppImageConfigName: string | undefined; -} - -/** - * @public - *The KernelGateway app settings.
- */ -export interface KernelGatewayAppSettings { - /** - * @public - *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
- *The Amazon SageMaker Studio UI does not use the default instance type value set here. The default - * instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation - * and the instance type parameter value is not passed.
- *A list of custom SageMaker images that are configured to run as a KernelGateway app.
- */ - CustomImages?: CustomImage[]; - - /** - * @public - *The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
- *To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
The JupyterServer app settings.
+ */ +export interface JupyterServerAppSettings { + /** + * @public + *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
+ */ + CodeRepositories?: CodeRepository[]; +} + +/** + * @public + *A custom SageMaker image. For more information, see + * Bring your own SageMaker image.
+ */ +export interface CustomImage { + /** + * @public + *The name of the CustomImage. Must be unique to your account.
+ */ + ImageName: string | undefined; + + /** + * @public + *The version number of the CustomImage.
+ */ + ImageVersionNumber?: number; + + /** + * @public + *The name of the AppImageConfig.
+ */ + AppImageConfigName: string | undefined; +} + +/** + * @public + *The KernelGateway app settings.
+ */ +export interface KernelGatewayAppSettings { + /** + * @public + *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
+ *The Amazon SageMaker Studio UI does not use the default instance type value set here. The default + * instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation + * and the instance type parameter value is not passed.
+ *A list of custom SageMaker images that are configured to run as a KernelGateway app.
+ */ + CustomImages?: CustomImage[]; + + /** + * @public + *The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
+ *To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A collection of settings that apply to spaces created in the Domain.
@@ -862,8 +946,8 @@ export interface DataCaptureConfig { /** * @public - *The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints - * with high traffic.
+ *The percentage of requests SageMaker will capture. A lower value is recommended + * for Endpoints with high traffic.
*/ InitialSamplingPercentage: number | undefined; @@ -875,8 +959,9 @@ export interface DataCaptureConfig { /** * @public - *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that - * SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
+ *The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker + * uses to encrypt the captured data at rest using Amazon S3 server-side + * encryption.
*The KmsKeyId can be any of the following formats:
*Configuration specifying how to treat different headers. If no headers are specified - * SageMaker will by default base64 encode when capturing the data.
+ * SageMaker will by default base64 encode when capturing the data. */ CaptureContentTypeHeader?: CaptureContentTypeHeader; } @@ -1331,6 +1416,36 @@ export interface FeatureDefinition { *The value type of a feature. Valid values are Integral, Fractional, or String.
*/ FeatureType?: FeatureType | string; + + /** + * @public + *A grouping of elements where each element within the collection must have the same
+ * feature type (String, Integral, or
+ * Fractional).
+ * List: An ordered collection of elements.
+ * Set: An unordered collection of unique elements.
+ * Vector: A specialized list that represents a fixed-size array of
+ * elements. The vector dimension is determined by you. Must have elements with
+ * fractional feature types.
Configuration for your collection.
+ */ + CollectionConfig?: CollectionConfig; } /** @@ -1533,6 +1648,20 @@ export interface OnlineStoreSecurityConfig { KmsKeyId?: string; } +/** + * @public + * @enum + */ +export const StorageType = { + IN_MEMORY: "InMemory", + STANDARD: "Standard", +} as const; + +/** + * @public + */ +export type StorageType = (typeof StorageType)[keyof typeof StorageType]; + /** * @public * @enum @@ -1604,6 +1733,23 @@ export interface OnlineStoreConfig { * information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide. */ TtlDuration?: TtlDuration; + + /** + * @public + *Option for different tiers of low latency storage for real-time data retrieval.
+ *
+ * Standard: A managed low latency data store for feature groups.
+ * InMemory: A managed data store for feature groups that supports very
+ * low latency retrieval.
Configuration specifying how to treat different headers. If no headers are specified - * SageMaker will by default base64 encode when capturing the data.
+ * Amazon SageMaker will by default base64 encode when capturing the data. */ ContentType?: CaptureContentTypeHeader; } @@ -7330,7 +7476,8 @@ export interface ModelBiasJobInput { export interface CreateModelBiasJobDefinitionRequest { /** * @public - *The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
+ *The name of the bias job definition. The name must be unique within an Amazon Web Services + * Region in the Amazon Web Services account.
*/ JobDefinitionName: string | undefined; @@ -7372,8 +7519,8 @@ export interface CreateModelBiasJobDefinitionRequest { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to - * perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; @@ -7385,8 +7532,9 @@ export interface CreateModelBiasJobDefinitionRequest { /** * @public - *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost - * Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see + * + * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
*/ Tags?: Tag[]; } @@ -7564,8 +7712,8 @@ export interface ModelExplainabilityAppSpecification { /** * @public - *JSON formatted S3 file that defines explainability parameters. For more information on - * this JSON configuration file, see Configure model explainability parameters.
+ *JSON formatted Amazon S3 file that defines explainability parameters. For more + * information on this JSON configuration file, see Configure model explainability parameters.
*/ ConfigUri: string | undefined; @@ -7631,8 +7779,7 @@ export interface CreateModelExplainabilityJobDefinitionRequest { /** * @public - *Configures the model explainability job to run a specified Docker container - * image.
+ *Configures the model explainability job to run a specified Docker container image.
*/ ModelExplainabilityAppSpecification: ModelExplainabilityAppSpecification | undefined; @@ -7662,8 +7809,8 @@ export interface CreateModelExplainabilityJobDefinitionRequest { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to - * perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; @@ -7675,8 +7822,9 @@ export interface CreateModelExplainabilityJobDefinitionRequest { /** * @public - *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost - * Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see + * + * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
*/ Tags?: Tag[]; } @@ -8129,17 +8277,17 @@ export interface CreateModelPackageInput { /** * @public *The machine learning domain of your model package and its components. Common - * machine learning domains include computer vision and natural language processing.
+ * machine learning domains include computer vision and natural language processing. */ Domain?: string; /** * @public *The machine learning task your model package accomplishes. Common machine
- * learning tasks include object detection and image classification. The following
- * tasks are supported by Inference Recommender:
- * "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" |
- * "FILL_MASK" | "CLASSIFICATION" | "REGRESSION" | "OTHER".
"IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" |
+ * "FILL_MASK" | "CLASSIFICATION" | "REGRESSION" | "OTHER".
* Specify "OTHER" if none of the tasks listed fit your use case.
*/ Task?: string; @@ -8147,18 +8295,18 @@ export interface CreateModelPackageInput { /** * @public *The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point - * to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files - * that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the - * InvokeEndpoint call.
+ * to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files + * that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the + * InvokeEndpoint call. */ SamplePayloadUrl?: string; /** * @public *An array of additional Inference Specification objects. Each additional - * Inference Specification specifies artifacts based on this model package that can - * be used on inference endpoints. Generally used with SageMaker Neo to store the - * compiled artifacts.
+ * Inference Specification specifies artifacts based on this model package that can + * be used on inference endpoints. Generally used with SageMaker Neo to store the + * compiled artifacts. */ AdditionalInferenceSpecifications?: AdditionalInferenceSpecificationDefinition[]; @@ -8257,16 +8405,15 @@ export interface ModelQualityAppSpecification { /** * @public *An Amazon S3 URI to a script that is called per row prior to running analysis. It can - * base64 decode the payload and convert it into a flatted json so that the built-in container - * can use the converted data. Applicable only for the built-in (first party) - * containers.
+ * base64 decode the payload and convert it into a flattened JSON so that the built-in container can use + * the converted data. Applicable only for the built-in (first party) containers. */ RecordPreprocessorSourceUri?: string; /** * @public - *An Amazon S3 URI to a script that is called after analysis has been performed. - * Applicable only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable + * only for the built-in (first party) containers.
*/ PostAnalyticsProcessorSourceUri?: string; @@ -8285,9 +8432,9 @@ export interface ModelQualityAppSpecification { /** * @public - *Configuration for monitoring constraints and monitoring statistics. These baseline - * resources are compared against the results of the current job from the series of jobs - * scheduled to collect data periodically.
+ *Configuration for monitoring constraints and monitoring statistics. These baseline resources are + * compared against the results of the current job from the series of jobs scheduled to collect data + * periodically.
*/ export interface ModelQualityBaselineConfig { /** @@ -8305,7 +8452,7 @@ export interface ModelQualityBaselineConfig { /** * @public - *The input for the model quality monitoring job. Currently endponts are supported for + *
The input for the model quality monitoring job. Currently endpoints are supported for * input for model quality monitoring jobs.
*/ export interface ModelQualityJobInput { @@ -8376,8 +8523,8 @@ export interface CreateModelQualityJobDefinitionRequest { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to - * perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; @@ -8389,8 +8536,9 @@ export interface CreateModelQualityJobDefinitionRequest { /** * @public - *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost - * Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see + * + * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
*/ Tags?: Tag[]; } @@ -8408,9 +8556,9 @@ export interface CreateModelQualityJobDefinitionResponse { /** * @public - *Configuration for monitoring constraints and monitoring statistics. These baseline - * resources are compared against the results of the current job from the series of jobs - * scheduled to collect data periodically.
+ *Configuration for monitoring constraints and monitoring statistics. These baseline resources are + * compared against the results of the current job from the series of jobs scheduled to collect data + * periodically.
*/ export interface MonitoringBaselineConfig { /** @@ -8428,8 +8576,8 @@ export interface MonitoringBaselineConfig { /** * @public - *The baseline statistics file in Amazon S3 that the current monitoring job should be - * validated against.
+ *The baseline statistics file in Amazon S3 that the current monitoring job should + * be validated against.
*/ StatisticsResource?: MonitoringStatisticsResource; } @@ -8460,16 +8608,15 @@ export interface MonitoringAppSpecification { /** * @public *An Amazon S3 URI to a script that is called per row prior to running analysis. It can - * base64 decode the payload and convert it into a flatted json so that the built-in container - * can use the converted data. Applicable only for the built-in (first party) - * containers.
+ * base64 decode the payload and convert it into a flattened JSON so that the built-in container can use + * the converted data. Applicable only for the built-in (first party) containers. */ RecordPreprocessorSourceUri?: string; /** * @public - *An Amazon S3 URI to a script that is called after analysis has been performed. - * Applicable only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable + * only for the built-in (first party) containers.
*/ PostAnalyticsProcessorSourceUri?: string; } @@ -8538,15 +8685,13 @@ export interface MonitoringJobDefinition { /** * @public - *The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker - * Endpoint.
+ *The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
*/ MonitoringInputs: MonitoringInput[] | undefined; /** * @public - *The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage - * Service (Amazon S3).
+ *The array of outputs from the monitoring job to be uploaded to Amazon S3.
*/ MonitoringOutputConfig: MonitoringOutputConfig | undefined; @@ -8583,8 +8728,8 @@ export interface MonitoringJobDefinition { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on - * your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; } @@ -8627,6 +8772,13 @@ export interface ScheduleConfig { *cron(0 [00-23] ? * * *)
*
* If you want to run the job one time, immediately, use the following + * keyword:
+ *
+ * NOW
+ *
For example, the following are valid cron expressions:
*You can also specify the keyword NOW to run the monitoring job immediately, one time,
- * without recurring.
You can also specify the keyword NOW to run the monitoring job immediately,
+ * one time, without recurring.
The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
+ *The name of the monitoring schedule. The name must be unique within an Amazon Web Services + * Region within an Amazon Web Services account.
*/ MonitoringScheduleName: string | undefined; /** * @public - *The configuration object that specifies the monitoring schedule and defines the - * monitoring job.
+ *The configuration object that specifies the monitoring schedule and defines the monitoring + * job.
*/ MonitoringScheduleConfig: MonitoringScheduleConfig | undefined; @@ -11747,64 +11900,6 @@ export interface RetentionPolicy { HomeEfsFileSystem?: RetentionType | string; } -/** - * @public - */ -export interface DeleteDomainRequest { - /** - * @public - *The domain ID.
- */ - DomainId: string | undefined; - - /** - * @public - *The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. - * By default, all resources are retained (not automatically deleted). - *
- */ - RetentionPolicy?: RetentionPolicy; -} - -/** - * @public - */ -export interface DeleteEdgeDeploymentPlanRequest { - /** - * @public - *The name of the edge deployment plan to delete.
- */ - EdgeDeploymentPlanName: string | undefined; -} - -/** - * @public - */ -export interface DeleteEdgeDeploymentStageRequest { - /** - * @public - *The name of the edge deployment plan from which the stage will be deleted.
- */ - EdgeDeploymentPlanName: string | undefined; - - /** - * @public - *The name of the stage.
- */ - StageName: string | undefined; -} - -/** - * @public - */ -export interface DeleteEndpointInput { - /** - * @public - *The name of the endpoint that you want to delete.
- */ - EndpointName: string | undefined; -} - /** * @internal */ diff --git a/clients/client-sagemaker/src/models/models_2.ts b/clients/client-sagemaker/src/models/models_2.ts index 16f50cb4b311..0603a52cdf07 100644 --- a/clients/client-sagemaker/src/models/models_2.ts +++ b/clients/client-sagemaker/src/models/models_2.ts @@ -159,6 +159,7 @@ import { RecommendationJobInputConfig, RecommendationJobStoppingConditions, RecommendationJobType, + RetentionPolicy, RetryStrategy, RootAccess, RuleEvaluationStatus, @@ -177,6 +178,64 @@ import { VendorGuidance, } from "./models_1"; +/** + * @public + */ +export interface DeleteDomainRequest { + /** + * @public + *The domain ID.
+ */ + DomainId: string | undefined; + + /** + * @public + *The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. + * By default, all resources are retained (not automatically deleted). + *
+ */ + RetentionPolicy?: RetentionPolicy; +} + +/** + * @public + */ +export interface DeleteEdgeDeploymentPlanRequest { + /** + * @public + *The name of the edge deployment plan to delete.
+ */ + EdgeDeploymentPlanName: string | undefined; +} + +/** + * @public + */ +export interface DeleteEdgeDeploymentStageRequest { + /** + * @public + *The name of the edge deployment plan from which the stage will be deleted.
+ */ + EdgeDeploymentPlanName: string | undefined; + + /** + * @public + *The name of the stage.
+ */ + StageName: string | undefined; +} + +/** + * @public + */ +export interface DeleteEndpointInput { + /** + * @public + *The name of the endpoint that you want to delete.
+ */ + EndpointName: string | undefined; +} + /** * @public */ @@ -2049,8 +2108,8 @@ export interface DescribeDataQualityJobDefinitionResponse { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to - * perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; @@ -5858,7 +5917,8 @@ export interface DescribeModelBiasJobDefinitionResponse { /** * @public - *The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
+ *The name of the bias job definition. The name must be unique within an Amazon Web Services + * Region in the Amazon Web Services account.
*/ JobDefinitionName: string | undefined; @@ -5906,9 +5966,8 @@ export interface DescribeModelBiasJobDefinitionResponse { /** * @public - *The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management - * (IAM) role that has read permission to the input data location and write permission to the - * output data location in Amazon S3.
+ *The Amazon Resource Name (ARN) of the IAM role that has read permission to the + * input data location and write permission to the output data location in Amazon S3.
*/ RoleArn: string | undefined; @@ -6233,8 +6292,7 @@ export interface DescribeModelExplainabilityJobDefinitionResponse { /** * @public - *Configures the model explainability job to run a specified Docker container - * image.
+ *Configures the model explainability job to run a specified Docker container image.
*/ ModelExplainabilityAppSpecification: ModelExplainabilityAppSpecification | undefined; @@ -6264,9 +6322,8 @@ export interface DescribeModelExplainabilityJobDefinitionResponse { /** * @public - *The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management - * (IAM) role that has read permission to the input data location and write permission to the - * output data location in Amazon S3.
+ *The Amazon Resource Name (ARN) of the IAM role that has read permission to the + * input data location and write permission to the output data location in Amazon S3.
*/ RoleArn: string | undefined; @@ -6488,29 +6545,29 @@ export interface DescribeModelPackageOutput { /** * @public *The machine learning domain of the model package you specified. Common machine - * learning domains include computer vision and natural language processing.
+ * learning domains include computer vision and natural language processing. */ Domain?: string; /** * @public *The machine learning task you specified that your model package accomplishes. - * Common machine learning tasks include object detection and image classification.
+ * Common machine learning tasks include object detection and image classification. */ Task?: string; /** * @public *The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single - * gzip compressed tar archive (.tar.gz suffix).
+ * gzip compressed tar archive (.tar.gz suffix). */ SamplePayloadUrl?: string; /** * @public *An array of additional Inference Specification objects. Each additional - * Inference Specification specifies artifacts based on this model package that can - * be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
+ * Inference Specification specifies artifacts based on this model package that can + * be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts. */ AdditionalInferenceSpecifications?: AdditionalInferenceSpecificationDefinition[]; @@ -6664,8 +6721,8 @@ export interface DescribeModelQualityJobDefinitionResponse { /** * @public - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to - * perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can + * assume to perform tasks on your behalf.
*/ RoleArn: string | undefined; @@ -6859,8 +6916,8 @@ export interface DescribeMonitoringScheduleResponse { /** * @public - *The configuration object that specifies the monitoring schedule and defines the - * monitoring job.
+ *The configuration object that specifies the monitoring schedule and defines the monitoring + * job.
*/ MonitoringScheduleConfig: MonitoringScheduleConfig | undefined; @@ -10926,212 +10983,6 @@ export interface Experiment { Tags?: Tag[]; } -/** - * @public - *A summary of the properties of an experiment. To get the complete set of properties, call
- * the DescribeExperiment API and provide the
- * ExperimentName.
The Amazon Resource Name (ARN) of the experiment.
- */ - ExperimentArn?: string; - - /** - * @public - *The name of the experiment.
- */ - ExperimentName?: string; - - /** - * @public - *The name of the experiment as displayed. If DisplayName isn't specified,
- * ExperimentName is displayed.
The source of the experiment.
- */ - ExperimentSource?: ExperimentSource; - - /** - * @public - *When the experiment was created.
- */ - CreationTime?: Date; - - /** - * @public - *When the experiment was last modified.
- */ - LastModifiedTime?: Date; -} - -/** - * @public - *The container for the metadata for Fail step.
- */ -export interface FailStepMetadata { - /** - * @public - *A message that you define and then is processed and rendered by - * the Fail step when the error occurs.
- */ - ErrorMessage?: string; -} - -/** - * @public - *Amazon SageMaker Feature Store stores features in a collection called Feature Group. A - * Feature Group can be visualized as a table which has rows, with a unique identifier for - * each row where each column in the table is a feature. In principle, a Feature Group is - * composed of features and values per features.
- */ -export interface FeatureGroup { - /** - * @public - *The Amazon Resource Name (ARN) of a FeatureGroup.
The name of the FeatureGroup.
The name of the Feature whose value uniquely identifies a
- * Record defined in the FeatureGroup
- * FeatureDefinitions.
The name of the feature that stores the EventTime of a Record in a
- * FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to
- * the creation or update of a Record in FeatureGroup. All
- * Records in the FeatureGroup must have a corresponding
- * EventTime.
A list of Features. Each Feature must include a
- * FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and
- * String.
- * FeatureNames cannot be any of the following: is_deleted,
- * write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per
- * FeatureGroup.
The time a FeatureGroup was created.
A timestamp indicating the last time you updated the feature group.
- */ - LastModifiedTime?: Date; - - /** - * @public - *Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or
- * KMSKeyId, for at rest data encryption. You can turn
- * OnlineStore on or off by specifying the EnableOnlineStore flag
- * at General Assembly.
The default value is False.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to
- * CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in
- * S3StorageConfig.
The Amazon Resource Name (ARN) of the IAM execution role used to create the feature - * group.
- */ - RoleArn?: string; - - /** - * @public - *A FeatureGroup status.
The status of OfflineStore.
A value that indicates whether the feature group was updated successfully.
- */ - LastUpdateStatus?: LastUpdateStatus; - - /** - * @public - *The reason that the FeatureGroup failed to be replicated in the
- * OfflineStore. This is failure may be due to a failure to create a
- * FeatureGroup in or delete a FeatureGroup from the
- * OfflineStore.
A free form description of a FeatureGroup.
Tags used to define a FeatureGroup.
A summary of the properties of an experiment. To get the complete set of properties, call
+ * the DescribeExperiment API and provide the
+ * ExperimentName.
The Amazon Resource Name (ARN) of the experiment.
+ */ + ExperimentArn?: string; + + /** + * @public + *The name of the experiment.
+ */ + ExperimentName?: string; + + /** + * @public + *The name of the experiment as displayed. If DisplayName isn't specified,
+ * ExperimentName is displayed.
The source of the experiment.
+ */ + ExperimentSource?: ExperimentSource; + + /** + * @public + *When the experiment was created.
+ */ + CreationTime?: Date; + + /** + * @public + *When the experiment was last modified.
+ */ + LastModifiedTime?: Date; +} + +/** + * @public + *The container for the metadata for Fail step.
+ */ +export interface FailStepMetadata { + /** + * @public + *A message that you define and then is processed and rendered by + * the Fail step when the error occurs.
+ */ + ErrorMessage?: string; +} + +/** + * @public + *Amazon SageMaker Feature Store stores features in a collection called Feature Group. A + * Feature Group can be visualized as a table which has rows, with a unique identifier for + * each row where each column in the table is a feature. In principle, a Feature Group is + * composed of features and values per features.
+ */ +export interface FeatureGroup { + /** + * @public + *The Amazon Resource Name (ARN) of a FeatureGroup.
The name of the FeatureGroup.
The name of the Feature whose value uniquely identifies a
+ * Record defined in the FeatureGroup
+ * FeatureDefinitions.
The name of the feature that stores the EventTime of a Record in a
+ * FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to
+ * the creation or update of a Record in FeatureGroup. All
+ * Records in the FeatureGroup must have a corresponding
+ * EventTime.
A list of Features. Each Feature must include a
+ * FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and
+ * String.
+ * FeatureNames cannot be any of the following: is_deleted,
+ * write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per
+ * FeatureGroup.
The time a FeatureGroup was created.
A timestamp indicating the last time you updated the feature group.
+ */ + LastModifiedTime?: Date; + + /** + * @public + *Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or
+ * KMSKeyId, for at rest data encryption. You can turn
+ * OnlineStore on or off by specifying the EnableOnlineStore flag
+ * at General Assembly.
The default value is False.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to
+ * CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in
+ * S3StorageConfig.
The Amazon Resource Name (ARN) of the IAM execution role used to create the feature + * group.
+ */ + RoleArn?: string; + + /** + * @public + *A FeatureGroup status.
The status of OfflineStore.
A value that indicates whether the feature group was updated successfully.
+ */ + LastUpdateStatus?: LastUpdateStatus; + + /** + * @public + *The reason that the FeatureGroup failed to be replicated in the
+ * OfflineStore. This is failure may be due to a failure to create a
+ * FeatureGroup in or delete a FeatureGroup from the
+ * OfflineStore.
A free form description of a FeatureGroup.
Tags used to define a FeatureGroup.
The sort order for results. The default is Descending.
Whether to sort the results in Ascending or Descending order.
+ * The default is Descending.
Whether to sort results by the Name or CreationTime field. The
- * default is CreationTime.
Whether to sort results by the Name or CreationTime field.
+ * The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Descending.
*/
SortOrder?: SortOrder | string;
/**
* @public
- * The token returned if the response is truncated. To retrieve the next set of job - * executions, use it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; @@ -5123,8 +5331,8 @@ export interface ListModelBiasJobDefinitionsResponse { /** * @public - *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, - * use it in the subsequent request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; } @@ -5607,22 +5815,22 @@ export interface ListModelExplainabilityJobDefinitionsRequest { /** * @public - *Whether to sort results by the Name or CreationTime field. The
- * default is CreationTime.
Whether to sort results by the Name or CreationTime field.
+ * The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Descending.
*/
SortOrder?: SortOrder | string;
/**
* @public
- * The token returned if the response is truncated. To retrieve the next set of job - * executions, use it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; @@ -5665,8 +5873,8 @@ export interface ListModelExplainabilityJobDefinitionsResponse { /** * @public - *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, - * use it in the subsequent request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; } @@ -6144,7 +6352,8 @@ export interface ListModelQualityJobDefinitionsRequest { /** * @public - *The sort order for results. The default is Descending.
Whether to sort the results in Ascending or Descending order.
+ * The default is Descending.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model - * quality monitoring job definitions, use it in the next request.
+ *If the response is truncated, Amazon SageMaker returns this token. To retrieve the + * next set of model quality monitoring job definitions, use it in the next request.
*/ NextToken?: string; } @@ -6607,22 +6816,22 @@ export interface ListMonitoringExecutionsRequest { /** * @public - *Whether to sort results by Status, CreationTime,
- * ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or
+ * ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Descending.
*/
SortOrder?: SortOrder | string;
/**
* @public
- * The token returned if the response is truncated. To retrieve the next set of job - * executions, use it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; @@ -6701,8 +6910,8 @@ export interface ListMonitoringExecutionsResponse { /** * @public - *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, - * use it in the subsequent reques
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; } @@ -6734,22 +6943,22 @@ export interface ListMonitoringSchedulesRequest { /** * @public - *Whether to sort results by Status, CreationTime,
- * ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or
+ * ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Descending.
*/
SortOrder?: SortOrder | string;
/**
* @public
- * The token returned if the response is truncated. To retrieve the next set of job - * executions, use it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; @@ -6876,8 +7085,8 @@ export interface ListMonitoringSchedulesResponse { /** * @public - *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs, - * use it in the subsequent request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use + * it in the next request.
*/ NextToken?: string; } @@ -10561,14 +10770,14 @@ export interface ModelPackage { /** * @public *The machine learning domain of your model package and its components. Common - * machine learning domains include computer vision and natural language processing.
+ * machine learning domains include computer vision and natural language processing. */ Domain?: string; /** * @public *The machine learning task your model package accomplishes. Common machine - * learning tasks include object detection and image classification.
+ * learning tasks include object detection and image classification. */ Task?: string; @@ -10611,151 +10820,6 @@ export interface ModelPackage { SkipModelValidation?: SkipModelValidation | string; } -/** - * @public - *A group of versioned models in the model registry.
- */ -export interface ModelPackageGroup { - /** - * @public - *The name of the model group.
- */ - ModelPackageGroupName?: string; - - /** - * @public - *The Amazon Resource Name (ARN) of the model group.
- */ - ModelPackageGroupArn?: string; - - /** - * @public - *The description for the model group.
- */ - ModelPackageGroupDescription?: string; - - /** - * @public - *The time that the model group was created.
- */ - CreationTime?: Date; - - /** - * @public - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
- */ - CreatedBy?: UserContext; - - /** - * @public - *The status of the model group. This can be one of the following values.
- *
- * PENDING - The model group is pending being created.
- * IN_PROGRESS - The model group is in the process of being
- * created.
- * COMPLETED - The model group was successfully created.
- * FAILED - The model group failed.
- * DELETING - The model group is in the process of being deleted.
- * DELETE_FAILED - SageMaker failed to delete the model group.
A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services - * resources in the Amazon Web Services General Reference Guide.
- */ - Tags?: Tag[]; -} - -/** - * @public - * @enum - */ -export const ModelVariantAction = { - PROMOTE: "Promote", - REMOVE: "Remove", - RETAIN: "Retain", -} as const; - -/** - * @public - */ -export type ModelVariantAction = (typeof ModelVariantAction)[keyof typeof ModelVariantAction]; - -/** - * @public - *A list of nested Filter objects. A resource must satisfy the conditions - * of all filters to be included in the results returned from the Search API.
- *For example, to filter on a training job's InputDataConfig property with a
- * specific channel name and S3Uri prefix, define the following filters:
- * '\{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"\}',
- *
- * '\{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains",
- * "Value":"mybucket/catdata"\}'
- *
The name of the property to use in the nested filters. The value must match a listed property name,
- * such as InputDataConfig.
A list of filters. Each filter acts on a property. Filters must contain at least one
- * Filters value. For example, a NestedFilters call might
- * include a filter on the PropertyName parameter of the
- * InputDataConfig property:
- * InputDataConfig.DataSource.S3DataSource.S3Uri.
Updates the feature group online store configuration.
- */ -export interface OnlineStoreConfigUpdate { - /** - * @public - *Time to live duration, where the record is hard deleted after the expiration time is
- * reached; ExpiresAt = EventTime + TtlDuration. For
- * information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
A group of versioned models in the model registry.
+ */ +export interface ModelPackageGroup { + /** + * @public + *The name of the model group.
+ */ + ModelPackageGroupName?: string; + + /** + * @public + *The Amazon Resource Name (ARN) of the model group.
+ */ + ModelPackageGroupArn?: string; + + /** + * @public + *The description for the model group.
+ */ + ModelPackageGroupDescription?: string; + + /** + * @public + *The time that the model group was created.
+ */ + CreationTime?: Date; + + /** + * @public + *Information about the user who created or modified an experiment, trial, trial + * component, lineage group, project, or model card.
+ */ + CreatedBy?: UserContext; + + /** + * @public + *The status of the model group. This can be one of the following values.
+ *
+ * PENDING - The model group is pending being created.
+ * IN_PROGRESS - The model group is in the process of being
+ * created.
+ * COMPLETED - The model group was successfully created.
+ * FAILED - The model group failed.
+ * DELETING - The model group is in the process of being deleted.
+ * DELETE_FAILED - SageMaker failed to delete the model group.
A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services + * resources in the Amazon Web Services General Reference Guide.
+ */ + Tags?: Tag[]; +} + +/** + * @public + * @enum + */ +export const ModelVariantAction = { + PROMOTE: "Promote", + REMOVE: "Remove", + RETAIN: "Retain", +} as const; + +/** + * @public + */ +export type ModelVariantAction = (typeof ModelVariantAction)[keyof typeof ModelVariantAction]; + +/** + * @public + *A list of nested Filter objects. A resource must satisfy the conditions + * of all filters to be included in the results returned from the Search API.
+ *For example, to filter on a training job's InputDataConfig property with a
+ * specific channel name and S3Uri prefix, define the following filters:
+ * '\{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"\}',
+ *
+ * '\{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains",
+ * "Value":"mybucket/catdata"\}'
+ *
The name of the property to use in the nested filters. The value must match a listed property name,
+ * such as InputDataConfig.
A list of filters. Each filter acts on a property. Filters must contain at least one
+ * Filters value. For example, a NestedFilters call might
+ * include a filter on the PropertyName parameter of the
+ * InputDataConfig property:
+ * InputDataConfig.DataSource.S3DataSource.S3Uri.
Updates the feature group online store configuration.
+ */ +export interface OnlineStoreConfigUpdate { + /** + * @public + *Time to live duration, where the record is hard deleted after the expiration time is
+ * reached; ExpiresAt = EventTime + TtlDuration. For
+ * information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
The trial that a trial component is associated with and the experiment the trial is part @@ -3218,14 +3361,15 @@ export interface UpdateMonitoringAlertResponse { export interface UpdateMonitoringScheduleRequest { /** * @public - *
The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
+ *The name of the monitoring schedule. The name must be unique within an Amazon Web Services + * Region within an Amazon Web Services account.
*/ MonitoringScheduleName: string | undefined; /** * @public - *The configuration object that specifies the monitoring schedule and defines the - * monitoring job.
+ *The configuration object that specifies the monitoring schedule and defines the monitoring + * job.
*/ MonitoringScheduleConfig: MonitoringScheduleConfig | undefined; } @@ -4035,6 +4179,7 @@ export interface SearchRequest { export const SearchRecordFilterSensitiveLog = (obj: SearchRecord): any => ({ ...obj, ...(obj.TrialComponent && { TrialComponent: obj.TrialComponent }), + ...(obj.FeatureGroup && { FeatureGroup: obj.FeatureGroup }), ...(obj.ModelCard && { ModelCard: ModelCardFilterSensitiveLog(obj.ModelCard) }), }); diff --git a/clients/client-sagemaker/src/protocols/Aws_json1_1.ts b/clients/client-sagemaker/src/protocols/Aws_json1_1.ts index 87e9806c4ed1..18ddc6c2c072 100644 --- a/clients/client-sagemaker/src/protocols/Aws_json1_1.ts +++ b/clients/client-sagemaker/src/protocols/Aws_json1_1.ts @@ -869,6 +869,7 @@ import { CodeRepositorySummary, CognitoConfig, CognitoMemberDefinition, + CollectionConfig, CollectionConfiguration, CompilationJobSummary, CompressionType, @@ -892,7 +893,6 @@ import { CreateContextRequest, CreateDataQualityJobDefinitionRequest, CreateDeviceFleetRequest, - CustomImage, DataQualityAppSpecification, DataQualityBaselineConfig, DataQualityJobInput, @@ -913,8 +913,6 @@ import { InputConfig, InstanceGroup, IntegerParameterRangeSpecification, - JupyterServerAppSettings, - KernelGatewayAppSettings, KernelGatewayImageConfig, KernelSpec, MetadataProperties, @@ -978,6 +976,7 @@ import { TransformOutput, TransformResources, TransformS3DataSource, + VectorConfig, VpcConfig, WorkspaceSettings, } from "../models/models_0"; @@ -1024,6 +1023,7 @@ import { CreateUserProfileRequest, CreateWorkforceRequest, CreateWorkteamRequest, + CustomImage, DataCaptureConfig, DataCatalogConfig, DataProcessing, @@ -1042,10 +1042,6 @@ import { DeleteContextRequest, DeleteDataQualityJobDefinitionRequest, DeleteDeviceFleetRequest, - DeleteDomainRequest, - DeleteEdgeDeploymentPlanRequest, - DeleteEdgeDeploymentStageRequest, - DeleteEndpointInput, DeploymentConfig, DeploymentStage, DeviceSelectionConfig, @@ -1085,6 +1081,8 @@ import { InferenceExperimentSchedule, InstanceMetadataServiceConfiguration, IntegerParameterRange, + JupyterServerAppSettings, + KernelGatewayAppSettings, LabelingJobAlgorithmsConfig, LabelingJobDataAttributes, LabelingJobDataSource, @@ -1194,7 +1192,11 @@ import { WorkforceVpcConfigRequest, } from "../models/models_1"; import { + DeleteDomainRequest, + DeleteEdgeDeploymentPlanRequest, + DeleteEdgeDeploymentStageRequest, DeleteEndpointConfigInput, + DeleteEndpointInput, DeleteExperimentRequest, DeleteFeatureGroupRequest, DeleteFlowDefinitionRequest, @@ -1362,8 +1364,6 @@ import { EndpointConfigSummary, EndpointSummary, Experiment, - ExperimentSummary, - FeatureGroup, FeatureParameter, FinalHyperParameterTuningJobObjectiveMetric, HyperParameterTrainingJobSummary, @@ -1390,6 +1390,8 @@ import { Workteam, } from "../models/models_2"; import { + ExperimentSummary, + FeatureGroup, FeatureGroupSummary, FeatureMetadata, Filter, @@ -1569,19 +1571,15 @@ import { ModelMetadataFilter, ModelMetadataSearchExpression, ModelPackage, - ModelPackageGroup, ModelPackageGroupSummary, ModelPackageSummary, ModelSummary, - ModelVariantAction, MonitoringAlertHistorySummary, MonitoringAlertSummary, MonitoringJobDefinitionSummary, MonitoringScheduleSummary, - NestedFilters, NotebookInstanceLifecycleConfigSummary, NotebookInstanceSummary, - OnlineStoreConfigUpdate, Parameter, PipelineExecutionStep, PipelineExecutionSummary, @@ -1603,6 +1601,10 @@ import { UserProfileDetails, } from "../models/models_3"; import { + ModelPackageGroup, + ModelVariantAction, + NestedFilters, + OnlineStoreConfigUpdate, Pipeline, PipelineExecution, ProcessingJob, @@ -19370,6 +19372,8 @@ const se_BatchTransformInput = (input: BatchTransformInput, context: __SerdeCont // se_CognitoMemberDefinition omitted. +// se_CollectionConfig omitted. + // se_CollectionConfiguration omitted. // se_CollectionConfigurations omitted. @@ -22201,6 +22205,8 @@ const se_UpdateTrialComponentRequest = (input: UpdateTrialComponentRequest, cont // se_VariantPropertyList omitted. +// se_VectorConfig omitted. + // se_VpcConfig omitted. // se_VpcSecurityGroupIds omitted. @@ -22739,6 +22745,8 @@ const de_CodeRepositorySummaryList = (output: any, context: __SerdeContext): Cod // de_CognitoMemberDefinition omitted. +// de_CollectionConfig omitted. + // de_CollectionConfiguration omitted. // de_CollectionConfigurations omitted. @@ -28541,6 +28549,8 @@ const de_UserProfileList = (output: any, context: __SerdeContext): UserProfileDe // de_UserSettings omitted. +// de_VectorConfig omitted. + // de_Vertex omitted. // de_Vertices omitted. diff --git a/codegen/sdk-codegen/aws-models/sagemaker.json b/codegen/sdk-codegen/aws-models/sagemaker.json index e47eb06ad182..05baaf51d9e4 100644 --- a/codegen/sdk-codegen/aws-models/sagemaker.json +++ b/codegen/sdk-codegen/aws-models/sagemaker.json @@ -4327,18 +4327,18 @@ "CsvContentTypes": { "target": "com.amazonaws.sagemaker#CsvContentTypes", "traits": { - "smithy.api#documentation": "The list of all content type headers that SageMaker will treat as CSV and capture\n accordingly.
" + "smithy.api#documentation": "The list of all content type headers that Amazon SageMaker will treat as CSV and\n capture accordingly.
" } }, "JsonContentTypes": { "target": "com.amazonaws.sagemaker#JsonContentTypes", "traits": { - "smithy.api#documentation": "The list of all content type headers that SageMaker will treat as JSON and capture\n accordingly.
" + "smithy.api#documentation": "The list of all content type headers that SageMaker will treat as JSON and\n capture accordingly.
" } } }, "traits": { - "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified\n SageMaker will by default base64 encode when capturing the data.
" + "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified\n Amazon SageMaker will by default base64 encode when capturing the data.
" } }, "com.amazonaws.sagemaker#CaptureMode": { @@ -5759,6 +5759,20 @@ "smithy.api#pattern": "^[\\w-]+_[0-9a-zA-Z]+$" } }, + "com.amazonaws.sagemaker#CollectionConfig": { + "type": "union", + "members": { + "VectorConfig": { + "target": "com.amazonaws.sagemaker#VectorConfig", + "traits": { + "smithy.api#documentation": "Configuration for your vector collection type.
\n\n Dimension: The number of elements in your vector.
Configuration for your collection.
" + } + }, "com.amazonaws.sagemaker#CollectionConfiguration": { "type": "structure", "members": { @@ -5816,6 +5830,29 @@ } } }, + "com.amazonaws.sagemaker#CollectionType": { + "type": "enum", + "members": { + "LIST": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "List" + } + }, + "SET": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "Set" + } + }, + "VECTOR": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "Vector" + } + } + } + }, "com.amazonaws.sagemaker#CompilationJobArn": { "type": "string", "traits": { @@ -6872,7 +6909,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
\nWe recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
\n\n CreateAutoMLJobV2 can manage tabular problem types identical to those of\n its previous version CreateAutoMLJob, as well as non-tabular problem types\n such as image or text classification.
Find guidelines about how to migrate a CreateAutoMLJob to\n CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
" + "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
\nWe recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
\n\n CreateAutoMLJobV2 can manage tabular problem types identical to those of\n its previous version CreateAutoMLJob, as well as time-series forecasting,\n and non-tabular problem types such as image or text classification.
Find guidelines about how to migrate a CreateAutoMLJob to\n CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
" } }, "com.amazonaws.sagemaker#CreateAutoMLJobRequest": { @@ -6980,7 +7017,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
\n\n CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob\n and DescribeAutoMLJob which offer backward compatibility.
\n\n CreateAutoMLJobV2 can manage tabular problem types identical to those of\n its previous version CreateAutoMLJob, as well as non-tabular problem types\n such as image or text classification.
Find guidelines about how to migrate a CreateAutoMLJob to\n CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see\n AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
" + "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
\n\n CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob\n and DescribeAutoMLJob which offer backward compatibility.
\n\n CreateAutoMLJobV2 can manage tabular problem types identical to those of\n its previous version CreateAutoMLJob, as well as time-series forecasting,\n and non-tabular problem types such as image or text classification.
Find guidelines about how to migrate a CreateAutoMLJob to\n CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see\n AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
" } }, "com.amazonaws.sagemaker#CreateAutoMLJobV2Request": { @@ -7316,7 +7353,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a definition for a job that monitors data quality and drift. For information\n about model monitor, see Amazon SageMaker Model Monitor.
" + "smithy.api#documentation": "Creates a definition for a job that monitors data quality and drift. For information\n about model monitor, see Amazon SageMaker Model\n Monitor.
" } }, "com.amazonaws.sagemaker#CreateDataQualityJobDefinitionRequest": { @@ -7370,7 +7407,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to\n perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -7380,7 +7417,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost\n Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -8974,7 +9011,7 @@ "JobDefinitionName": { "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionName", "traits": { - "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services \n Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -9019,7 +9056,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to\n perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -9029,7 +9066,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost\n Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -9241,7 +9278,7 @@ "ModelExplainabilityAppSpecification": { "target": "com.amazonaws.sagemaker#ModelExplainabilityAppSpecification", "traits": { - "smithy.api#documentation": "Configures the model explainability job to run a specified Docker container\n image.
", + "smithy.api#documentation": "Configures the model explainability job to run a specified Docker container image.
", "smithy.api#required": {} } }, @@ -9273,7 +9310,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to\n perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -9283,7 +9320,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost\n Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -9548,25 +9585,25 @@ "Domain": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning domain of your model package and its components. Common \n machine learning domains include computer vision and natural language processing.
" + "smithy.api#documentation": "The machine learning domain of your model package and its components. Common\n machine learning domains include computer vision and natural language processing.
" } }, "Task": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine \n learning tasks include object detection and image classification. The following \n tasks are supported by Inference Recommender: \n \"IMAGE_CLASSIFICATION\" | \"OBJECT_DETECTION\" | \"TEXT_GENERATION\" |\"IMAGE_SEGMENTATION\" | \n \"FILL_MASK\" | \"CLASSIFICATION\" | \"REGRESSION\" | \"OTHER\".
Specify \"OTHER\" if none of the tasks listed fit your use case.
" + "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine\n learning tasks include object detection and image classification. The following\n tasks are supported by Inference Recommender:\n \"IMAGE_CLASSIFICATION\" | \"OBJECT_DETECTION\" | \"TEXT_GENERATION\" |\"IMAGE_SEGMENTATION\" |\n \"FILL_MASK\" | \"CLASSIFICATION\" | \"REGRESSION\" | \"OTHER\".
Specify \"OTHER\" if none of the tasks listed fit your use case.
" } }, "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point \n to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files\n that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the\n InvokeEndpoint call.
" + "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point\n to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files\n that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the\n InvokeEndpoint call.
" } }, "AdditionalInferenceSpecifications": { "target": "com.amazonaws.sagemaker#AdditionalInferenceSpecifications", "traits": { - "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional \n Inference Specification specifies artifacts based on this model package that can \n be used on inference endpoints. Generally used with SageMaker Neo to store the \n compiled artifacts.
" + "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional\n Inference Specification specifies artifacts based on this model package that can\n be used on inference endpoints. Generally used with SageMaker Neo to store the\n compiled artifacts.
" } }, "SkipModelValidation": { @@ -9613,7 +9650,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a definition for a job that monitors model quality and drift. For information\n about model monitor, see Amazon SageMaker Model Monitor.
" + "smithy.api#documentation": "Creates a definition for a job that monitors model quality and drift. For information\n about model monitor, see Amazon SageMaker Model\n Monitor.
" } }, "com.amazonaws.sagemaker#CreateModelQualityJobDefinitionRequest": { @@ -9667,7 +9704,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to\n perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -9677,7 +9714,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost\n Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -9717,7 +9754,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data\n captured for an Amazon SageMaker Endpoint.
" + "smithy.api#documentation": "Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to\n monitor the data captured for an Amazon SageMaker Endpoint.
" } }, "com.amazonaws.sagemaker#CreateMonitoringScheduleRequest": { @@ -9726,14 +9763,14 @@ "MonitoringScheduleName": { "target": "com.amazonaws.sagemaker#MonitoringScheduleName", "traits": { - "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
", + "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services \n Region within an Amazon Web Services account.
", "smithy.api#required": {} } }, "MonitoringScheduleConfig": { "target": "com.amazonaws.sagemaker#MonitoringScheduleConfig", "traits": { - "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the\n monitoring job.
", + "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring \n job.
", "smithy.api#required": {} } }, @@ -11364,7 +11401,7 @@ "InitialSamplingPercentage": { "target": "com.amazonaws.sagemaker#SamplingPercentage", "traits": { - "smithy.api#documentation": "The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints\n with high traffic.
", + "smithy.api#documentation": "The percentage of requests SageMaker will capture. A lower value is recommended\n for Endpoints with high traffic.
", "smithy.api#required": {} } }, @@ -11378,7 +11415,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that\n SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
\nThe KmsKeyId can be any of the following formats:
\nKey ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker\n uses to encrypt the captured data at rest using Amazon S3 server-side\n encryption.
\nThe KmsKeyId can be any of the following formats:
\nKey ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
Configuration specifying how to treat different headers. If no headers are specified\n SageMaker will by default base64 encode when capturing the data.
" + "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified\n SageMaker will by default base64 encode when capturing the data.
" } } }, @@ -11558,13 +11595,13 @@ "RecordPreprocessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can\n base64 decode the payload and convert it into a flatted json so that the built-in container\n can use the converted data. Applicable only for the built-in (first party)\n containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can \n base64 decode the payload and convert it into a flattened JSON so that the built-in container can use \n the converted data. Applicable only for the built-in (first party) containers.
" } }, "PostAnalyticsProcessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed.\n Applicable only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable \n only for the built-in (first party) containers.
" } }, "Environment": { @@ -11595,7 +11632,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline\n resources are compared against the results of the current job from the series of jobs\n scheduled to collect data periodically.
" + "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are \n compared against the results of the current job from the series of jobs scheduled to collect data \n periodically.
" } }, "com.amazonaws.sagemaker#DataQualityJobInput": { @@ -15151,7 +15188,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to\n perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -17996,7 +18033,7 @@ "JobDefinitionName": { "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionName", "traits": { - "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services \n Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -18048,7 +18085,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management\n (IAM) role that has read permission to the input data location and write permission to the\n output data location in Amazon S3.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that has read permission to the \n input data location and write permission to the output data location in Amazon S3.
", "smithy.api#required": {} } }, @@ -18351,7 +18388,7 @@ "ModelExplainabilityAppSpecification": { "target": "com.amazonaws.sagemaker#ModelExplainabilityAppSpecification", "traits": { - "smithy.api#documentation": "Configures the model explainability job to run a specified Docker container\n image.
", + "smithy.api#documentation": "Configures the model explainability job to run a specified Docker container image.
", "smithy.api#required": {} } }, @@ -18383,7 +18420,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management\n (IAM) role that has read permission to the input data location and write permission to the\n output data location in Amazon S3.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that has read permission to the \n input data location and write permission to the output data location in Amazon S3.
", "smithy.api#required": {} } }, @@ -18714,25 +18751,25 @@ "Domain": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning domain of the model package you specified. Common machine \n learning domains include computer vision and natural language processing.
" + "smithy.api#documentation": "The machine learning domain of the model package you specified. Common machine\n learning domains include computer vision and natural language processing.
" } }, "Task": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning task you specified that your model package accomplishes. \n Common machine learning tasks include object detection and image classification.
" + "smithy.api#documentation": "The machine learning task you specified that your model package accomplishes.\n Common machine learning tasks include object detection and image classification.
" } }, "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single \n gzip compressed tar archive (.tar.gz suffix).
" + "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single\n gzip compressed tar archive (.tar.gz suffix).
" } }, "AdditionalInferenceSpecifications": { "target": "com.amazonaws.sagemaker#AdditionalInferenceSpecifications", "traits": { - "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional \n Inference Specification specifies artifacts based on this model package that can \n be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
" + "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional\n Inference Specification specifies artifacts based on this model package that can\n be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
" } }, "SkipModelValidation": { @@ -18843,7 +18880,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to\n perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -18940,7 +18977,7 @@ "MonitoringScheduleConfig": { "target": "com.amazonaws.sagemaker#MonitoringScheduleConfig", "traits": { - "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the\n monitoring job.
", + "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring \n job.
", "smithy.api#required": {} } }, @@ -21582,6 +21619,15 @@ "target": "com.amazonaws.sagemaker#Device" } }, + "com.amazonaws.sagemaker#Dimension": { + "type": "integer", + "traits": { + "smithy.api#range": { + "min": 1, + "max": 8192 + } + } + }, "com.amazonaws.sagemaker#DirectInternetAccess": { "type": "enum", "members": { @@ -22989,7 +23035,7 @@ "S3DataDistributionType": { "target": "com.amazonaws.sagemaker#ProcessingS3DataDistributionType", "traits": { - "smithy.api#documentation": "Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key.\n Defaults to FullyReplicated\n
Whether input data distributed in Amazon S3 is fully replicated or sharded by an\n Amazon S3 key. Defaults to FullyReplicated\n
The value type of a feature. Valid values are Integral, Fractional, or String.
" } + }, + "CollectionType": { + "target": "com.amazonaws.sagemaker#CollectionType", + "traits": { + "smithy.api#documentation": "A grouping of elements where each element within the collection must have the same\n feature type (String, Integral, or\n Fractional).
\n List: An ordered collection of elements.
\n Set: An unordered collection of unique elements.
\n Vector: A specialized list that represents a fixed-size array of\n elements. The vector dimension is determined by you. Must have elements with\n fractional feature types.
Configuration for your collection.
" + } } }, "traits": { @@ -25493,7 +25551,7 @@ "CountryCode": { "target": "com.amazonaws.sagemaker#CountryCode", "traits": { - "smithy.api#documentation": "The country code for the holiday calendar.
\nFor the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your\n choice.
" + "smithy.api#documentation": "The country code for the holiday calendar.
\nFor the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your\n choice.
" } } }, @@ -31483,7 +31541,7 @@ "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "The sort order for results. The default is Descending.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort results by the Name or CreationTime field. The\n default is CreationTime.
Whether to sort results by the Name or CreationTime field. \n The default is CreationTime.
Whether to sort the results in Ascending or Descending order.\n The default is Descending.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job\n executions, use it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } }, "MaxResults": { @@ -33986,7 +34044,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs,\n use it in the subsequent request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } } }, @@ -34329,19 +34387,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionSortKey", "traits": { - "smithy.api#documentation": "Whether to sort results by the Name or CreationTime field. The\n default is CreationTime.
Whether to sort results by the Name or CreationTime field. \n The default is CreationTime.
Whether to sort the results in Ascending or Descending order.\n The default is Descending.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job\n executions, use it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } }, "MaxResults": { @@ -34386,7 +34444,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs,\n use it in the subsequent request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } } }, @@ -34691,7 +34749,7 @@ "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "The sort order for results. The default is Descending.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model\n quality monitoring job definitions, use it in the next request.
" + "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the\n next set of model quality monitoring job definitions, use it in the next request.
" } } }, @@ -35050,19 +35108,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#MonitoringExecutionSortKey", "traits": { - "smithy.api#documentation": "Whether to sort results by Status, CreationTime,\n ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or \n ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.\n The default is Descending.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job\n executions, use it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } }, "MaxResults": { @@ -35143,7 +35201,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs,\n use it in the subsequent reques
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } } }, @@ -35181,19 +35239,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#MonitoringScheduleSortKey", "traits": { - "smithy.api#documentation": "Whether to sort results by Status, CreationTime,\n ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or \n ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.\n The default is Descending.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job\n executions, use it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } }, "MaxResults": { @@ -35268,7 +35326,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of jobs,\n use it in the subsequent request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" } } }, @@ -38924,7 +38982,7 @@ "ConfigUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "JSON formatted S3 file that defines explainability parameters. For more information on\n this JSON configuration file, see Configure model explainability parameters.
", + "smithy.api#documentation": "JSON formatted Amazon S3 file that defines explainability parameters. For more\n information on this JSON configuration file, see Configure model explainability parameters.
", "smithy.api#required": {} } }, @@ -39361,19 +39419,19 @@ "Domain": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning domain of your model package and its components. Common \n machine learning domains include computer vision and natural language processing.
" + "smithy.api#documentation": "The machine learning domain of your model package and its components. Common\n machine learning domains include computer vision and natural language processing.
" } }, "Task": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine \n learning tasks include object detection and image classification.
" + "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine\n learning tasks include object detection and image classification.
" } }, "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service path where the sample payload are stored. This path must point to \n a single gzip compressed tar archive (.tar.gz suffix).
" + "smithy.api#documentation": "The Amazon Simple Storage Service path where the sample payload are stored. This path must point to\n a single gzip compressed tar archive (.tar.gz suffix).
" } }, "AdditionalInferenceSpecifications": { @@ -40001,13 +40059,13 @@ "RecordPreprocessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can\n base64 decode the payload and convert it into a flatted json so that the built-in container\n can use the converted data. Applicable only for the built-in (first party)\n containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can \n base64 decode the payload and convert it into a flattened JSON so that the built-in container can use \n the converted data. Applicable only for the built-in (first party) containers.
" } }, "PostAnalyticsProcessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed.\n Applicable only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable \n only for the built-in (first party) containers.
" } }, "ProblemType": { @@ -40041,7 +40099,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline\n resources are compared against the results of the current job from the series of jobs\n scheduled to collect data periodically.
" + "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are \n compared against the results of the current job from the series of jobs scheduled to collect data \n periodically.
" } }, "com.amazonaws.sagemaker#ModelQualityJobInput": { @@ -40065,7 +40123,7 @@ } }, "traits": { - "smithy.api#documentation": "The input for the model quality monitoring job. Currently endponts are supported for\n input for model quality monitoring jobs.
" + "smithy.api#documentation": "The input for the model quality monitoring job. Currently endpoints are supported for\n input for model quality monitoring jobs.
" } }, "com.amazonaws.sagemaker#ModelRegisterSettings": { @@ -40522,13 +40580,13 @@ "RecordPreprocessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can\n base64 decode the payload and convert it into a flatted json so that the built-in container\n can use the converted data. Applicable only for the built-in (first party)\n containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can \n base64 decode the payload and convert it into a flattened JSON so that the built-in container can use \n the converted data. Applicable only for the built-in (first party) containers.
" } }, "PostAnalyticsProcessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed.\n Applicable only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable \n only for the built-in (first party) containers.
" } } }, @@ -40554,12 +40612,12 @@ "StatisticsResource": { "target": "com.amazonaws.sagemaker#MonitoringStatisticsResource", "traits": { - "smithy.api#documentation": "The baseline statistics file in Amazon S3 that the current monitoring job should be\n validated against.
" + "smithy.api#documentation": "The baseline statistics file in Amazon S3 that the current monitoring job should\n be validated against.
" } } }, "traits": { - "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline\n resources are compared against the results of the current job from the series of jobs\n scheduled to collect data periodically.
" + "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are \n compared against the results of the current job from the series of jobs scheduled to collect data \n periodically.
" } }, "com.amazonaws.sagemaker#MonitoringClusterConfig": { @@ -40589,7 +40647,7 @@ "VolumeKmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon\n SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s)\n that run the model monitoring job.
" + "smithy.api#documentation": "The Key Management Service (KMS) key that Amazon SageMaker uses to\n encrypt data on the storage volume attached to the ML compute instance(s) that run the\n model monitoring job.
" } } }, @@ -40857,14 +40915,14 @@ "MonitoringInputs": { "target": "com.amazonaws.sagemaker#MonitoringInputs", "traits": { - "smithy.api#documentation": "The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker\n Endpoint.
", + "smithy.api#documentation": "The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
", "smithy.api#required": {} } }, "MonitoringOutputConfig": { "target": "com.amazonaws.sagemaker#MonitoringOutputConfig", "traits": { - "smithy.api#documentation": "The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage\n Service (Amazon S3).
", + "smithy.api#documentation": "The array of outputs from the monitoring job to be uploaded to Amazon S3.
", "smithy.api#required": {} } }, @@ -40903,7 +40961,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on\n your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can \n assume to perform tasks on your behalf.
", "smithy.api#required": {} } } @@ -40998,7 +41056,7 @@ "target": "com.amazonaws.sagemaker#Boolean", "traits": { "smithy.api#default": false, - "smithy.api#documentation": "Indicates if the file should be read as a json object per line.
" + "smithy.api#documentation": "Indicates if the file should be read as a JSON object per line.
" } } }, @@ -41047,7 +41105,7 @@ "S3Output": { "target": "com.amazonaws.sagemaker#MonitoringS3Output", "traits": { - "smithy.api#documentation": "The Amazon S3 storage location where the results of a monitoring job are saved.
", + "smithy.api#documentation": "The Amazon S3 storage location where the results of a monitoring job are\n saved.
", "smithy.api#required": {} } } @@ -41069,7 +41127,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker\n uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
" + "smithy.api#documentation": "The Key Management Service (KMS) key that Amazon SageMaker uses to\n encrypt the model artifacts at rest using Amazon S3 server-side encryption.
" } } }, @@ -41140,14 +41198,14 @@ "S3Uri": { "target": "com.amazonaws.sagemaker#MonitoringS3Uri", "traits": { - "smithy.api#documentation": "A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a\n monitoring job.
", + "smithy.api#documentation": "A URI that identifies the Amazon S3 storage location where Amazon SageMaker\n saves the results of a monitoring job.
", "smithy.api#required": {} } }, "LocalPath": { "target": "com.amazonaws.sagemaker#ProcessingLocalPath", "traits": { - "smithy.api#documentation": "The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a\n monitoring job. LocalPath is an absolute path for the output data.
", + "smithy.api#documentation": "The local path to the Amazon S3 storage location where Amazon SageMaker\n saves the results of a monitoring job. LocalPath is an absolute path for the output\n data.
", "smithy.api#required": {} } }, @@ -42378,6 +42436,12 @@ "traits": { "smithy.api#documentation": "Time to live duration, where the record is hard deleted after the expiration time is\n reached; ExpiresAt = EventTime + TtlDuration. For\n information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Option for different tiers of low latency storage for real-time data retrieval.
\n\n Standard: A managed low latency data store for feature groups.
\n InMemory: A managed data store for feature groups that supports very\n low latency retrieval.
A cron expression that describes details about the monitoring schedule.
\nThe supported cron expressions are:
\nIf you want to set the job to start every hour, use the following:
\n\n Hourly: cron(0 * ? * * *)\n
If you want to start the job daily:
\n\n cron(0 [00-23] ? * * *)\n
For example, the following are valid cron expressions:
\nDaily at noon UTC: cron(0 12 ? * * *)\n
Daily at midnight UTC: cron(0 0 ? * * *)\n
To support running every 6, 12 hours, the following are also supported:
\n\n cron(0 [00-23]/[01-24] ? * * *)\n
For example, the following are valid cron expressions:
\nEvery 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)\n
Every two hours starting at midnight: cron(0 0/2 ? * * *)\n
Even though the cron expression is set to start at 5PM UTC, note that there\n could be a delay of 0-20 minutes from the actual requested time to run the\n execution.
\nWe recommend that if you would like a daily schedule, you do not provide this\n parameter. Amazon SageMaker will pick a time for running every day.
\nYou can also specify the keyword NOW to run the monitoring job immediately, one time,\n without recurring.
A cron expression that describes details about the monitoring schedule.
\nThe supported cron expressions are:
\nIf you want to set the job to start every hour, use the following:
\n\n Hourly: cron(0 * ? * * *)\n
If you want to start the job daily:
\n\n cron(0 [00-23] ? * * *)\n
If you want to run the job one time, immediately, use the following\n keyword:
\n\n NOW\n
For example, the following are valid cron expressions:
\nDaily at noon UTC: cron(0 12 ? * * *)\n
Daily at midnight UTC: cron(0 0 ? * * *)\n
To support running every 6, 12 hours, the following are also supported:
\n\n cron(0 [00-23]/[01-24] ? * * *)\n
For example, the following are valid cron expressions:
\nEvery 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)\n
Every two hours starting at midnight: cron(0 0/2 ? * * *)\n
Even though the cron expression is set to start at 5PM UTC, note that there\n could be a delay of 0-20 minutes from the actual requested time to run the\n execution.
\nWe recommend that if you would like a daily schedule, you do not provide this\n parameter. Amazon SageMaker will pick a time for running every day.
\nYou can also specify the keyword NOW to run the monitoring job immediately,\n one time, without recurring.
Specifies a limit to how long a model training job or model compilation job can run.\n It also specifies how long a managed spot training job has to complete. When the job\n reaches the time limit, SageMaker ends the training or compilation job. Use this API to cap\n model training costs.
\nTo stop a training job, SageMaker sends the algorithm the SIGTERM signal,\n which delays job termination for 120 seconds. Algorithms can use this 120-second window\n to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results\n of a model training job when possible. This attempt to save artifacts is only a best\n effort case as model might not be in a state from which it can be saved. For example, if\n training has just started, the model might not be ready to save. When saved, this\n intermediate data is a valid model artifact. You can use it to create a model with\n CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model\n artifacts. When training NTMs, make sure that the maximum runtime is sufficient for\n the training job to complete.
\nThe collection of holidays featurization attributes used to incorporate national holiday\n information into your forecasting model.
" + "smithy.api#documentation": "The collection of holiday featurization attributes used to incorporate national holiday\n information into your forecasting model.
" } } }, @@ -58108,7 +58189,7 @@ "FeatureGroupName": { "target": "com.amazonaws.sagemaker#FeatureGroupNameOrArn", "traits": { - "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the feature group containing the feature that \n you're updating.
", + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the feature group containing the feature that\n you're updating.
", "smithy.api#required": {} } }, @@ -58716,14 +58797,14 @@ "MonitoringScheduleName": { "target": "com.amazonaws.sagemaker#MonitoringScheduleName", "traits": { - "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
", + "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services \n Region within an Amazon Web Services account.
", "smithy.api#required": {} } }, "MonitoringScheduleConfig": { "target": "com.amazonaws.sagemaker#MonitoringScheduleConfig", "traits": { - "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the\n monitoring job.
", + "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring \n job.
", "smithy.api#required": {} } } @@ -59993,6 +60074,21 @@ } } }, + "com.amazonaws.sagemaker#VectorConfig": { + "type": "structure", + "members": { + "Dimension": { + "target": "com.amazonaws.sagemaker#Dimension", + "traits": { + "smithy.api#documentation": "The number of elements in your vector.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "Configuration for your vector collection type.
" + } + }, "com.amazonaws.sagemaker#VendorGuidance": { "type": "enum", "members": {