CreateModelBiasJobDefinition - Amazon SageMaker
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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": { "BatchTransformInput": { "DataCapturedDestinationS3Uri": "string", "DatasetFormat": { "Csv": { "Header": boolean }, "Json": { "Line": boolean }, "Parquet": { } }, "EndTimeOffset": "string", "ExcludeFeaturesAttribute": "string", "FeaturesAttribute": "string", "InferenceAttribute": "string", "LocalPath": "string", "ProbabilityAttribute": "string", "ProbabilityThresholdAttribute": number, "S3DataDistributionType": "string", "S3InputMode": "string", "StartTimeOffset": "string" }, "EndpointInput": { "EndpointName": "string", "EndTimeOffset": "string", "ExcludeFeaturesAttribute": "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.


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]){0,62}$

Required: Yes


Identifies the resources to deploy for a monitoring job.

Type: MonitoringResources object

Required: Yes


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

Type: ModelBiasAppSpecification object

Required: Yes


The baseline configuration for a model bias job.

Type: ModelBiasBaselineConfig object

Required: No


Inputs for the model bias job.

Type: ModelBiasJobInput object

Required: Yes


The output configuration for monitoring jobs.

Type: MonitoringOutputConfig object

Required: Yes


Networking options for a model bias job.

Type: MonitoringNetworkConfig object

Required: No


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


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

Type: MonitoringStoppingCondition object

Required: No


(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.


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

Type: String

Length Constraints: Maximum length of 256.

Pattern: .*


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


Resource being accessed is in use.

HTTP Status Code: 400


You have exceeded an 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: