CreateModelBiasJobDefinition - Amazon SageMaker
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China.

CreateModelBiasJobDefinition

Creates the definition for a model bias job.

Request Syntax

{ "JobDefinitionName": "string", "JobResources": { "ClusterConfig": { "InstanceCount": number, "InstanceType": "string", "VolumeKmsKeyId": "string", "VolumeSizeInGB": number } }, "ModelBiasAppSpecification": { "ConfigUri": "string", "Environment": { "string" : "string" }, "ImageUri": "string" }, "ModelBiasBaselineConfig": { "BaseliningJobName": "string", "ConstraintsResource": { "S3Uri": "string" } }, "ModelBiasJobInput": { "EndpointInput": { "EndpointName": "string", "EndTimeOffset": "string", "FeaturesAttribute": "string", "InferenceAttribute": "string", "LocalPath": "string", "ProbabilityAttribute": "string", "ProbabilityThresholdAttribute": number, "S3DataDistributionType": "string", "S3InputMode": "string", "StartTimeOffset": "string" }, "GroundTruthS3Input": { "S3Uri": "string" } }, "ModelBiasJobOutputConfig": { "KmsKeyId": "string", "MonitoringOutputs": [ { "S3Output": { "LocalPath": "string", "S3UploadMode": "string", "S3Uri": "string" } } ] }, "NetworkConfig": { "EnableInterContainerTrafficEncryption": boolean, "EnableNetworkIsolation": boolean, "VpcConfig": { "SecurityGroupIds": [ "string" ], "Subnets": [ "string" ] } }, "RoleArn": "string", "StoppingCondition": { "MaxRuntimeInSeconds": number }, "Tags": [ { "Key": "string", "Value": "string" } ] }

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.

JobDefinitionName

The name of the bias job definition. The name must be unique within an Amazon Region in the Amazon account.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9])*$

Required: Yes

JobResources

Identifies the resources to deploy for a monitoring job.

Type: MonitoringResources object

Required: Yes

ModelBiasAppSpecification

Configures the model bias job to run a specified Docker container image.

Type: ModelBiasAppSpecification object

Required: Yes

ModelBiasBaselineConfig

The baseline configuration for a model bias job.

Type: ModelBiasBaselineConfig object

Required: No

ModelBiasJobInput

Inputs for the model bias job.

Type: ModelBiasJobInput object

Required: Yes

ModelBiasJobOutputConfig

The output configuration for monitoring jobs.

Type: MonitoringOutputConfig object

Required: Yes

NetworkConfig

Networking options for a model bias job.

Type: MonitoringNetworkConfig object

Required: No

RoleArn

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: Yes

StoppingCondition

A time limit for how long the monitoring job is allowed to run before stopping.

Type: MonitoringStoppingCondition object

Required: No

Tags

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Billing and Cost Management User Guide.

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

Response Syntax

{ "JobDefinitionArn": "string" }

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.

JobDefinitionArn

The Amazon Resource Name (ARN) of the model bias job.

Type: String

Length Constraints: Maximum length of 256.

Pattern: .*

Errors

For information about the errors that are common to all actions, see Common Errors.

ResourceInUse

Resource being accessed is in use.

HTTP Status Code: 400

ResourceLimitExceeded

You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific Amazon SDKs, see the following: