CreateModelBiasJobDefinition
Service: Amazon SageMaker Service Creates the definition for a model bias job.
Request Syntax
{
"JobDefinitionName": "string", "JobResources": {
"ModelBiasAppSpecification": { "ConfigUri": "string",
"ModelBiasBaselineConfig": { "BaseliningJobName": "string", "ConstraintsResource": { "S3Uri": "string"
} },
"ModelBiasJobInput": { "EndpointInput": {
"ProbabilityAttribute": "string", "ProbabilityThresholdAttribute": number, "S3DataDistributionType": "string", "S3InputMode": "string",
"ModelBiasJobOutputConfig": { "KmsKeyId": "string",
"EnableInterContainerTrafficEncryption": boolean, "EnableNetworkIsolation": boolean,
"VpcConfig": {
CreateModelBiasJobDefinition
"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 (p. 1463).
The request accepts the following data in JSON format.
JobDefinitionName (p. 117)
The name of the bias job definition. The name must be unique within an AWS Region in the AWS 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 (p. 117)
Identifies the resources to deploy for a monitoring job.
Type: MonitoringResources (p. 1204) object Required: Yes
ModelBiasAppSpecification (p. 117)
Configures the model bias job to run a specified Docker container image.
Type: ModelBiasAppSpecification (p. 1144) object Required: Yes
ModelBiasBaselineConfig (p. 117)
The baseline configuration for a model bias job.
Type: ModelBiasBaselineConfig (p. 1145) object Required: No
ModelBiasJobInput (p. 117) Inputs for the model bias job.
Type: ModelBiasJobInput (p. 1146) object
CreateModelBiasJobDefinition
Required: Yes
ModelBiasJobOutputConfig (p. 117)
The output configuration for monitoring jobs.
Type: MonitoringOutputConfig (p. 1203) object Required: Yes
NetworkConfig (p. 117)
Networking options for a model bias job.
Type: MonitoringNetworkConfig (p. 1201) object Required: No
RoleArn (p. 117)
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 (p. 117)
A time limit for how long the monitoring job is allowed to run before stopping.
Type: MonitoringStoppingCondition (p. 1213) object Required: No
Tags (p. 117)
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
Type: Array of Tag (p. 1370) 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.
CreateModelBiasJobDefinition
JobDefinitionArn (p. 119)
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 (p. 1465).
ResourceInUse
Resource being accessed is in use.
HTTP Status Code: 400 ResourceLimitExceeded
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 AWS SDKs, see the following:
• AWS Command Line Interface
• AWS SDK for .NET
• AWS SDK for C++
• AWS SDK for Go
• AWS SDK for Java V2
• AWS SDK for JavaScript
• AWS SDK for PHP V3
• AWS SDK for Python
• AWS SDK for Ruby V3
CreateModelExplainabilityJobDefinition
CreateModelExplainabilityJobDefinition
Service: Amazon SageMaker Service
Creates the definition for a model explainability job.
Request Syntax
{
"JobDefinitionName": "string", "JobResources": {
"ModelExplainabilityAppSpecification": { "ConfigUri": "string",
"ModelExplainabilityBaselineConfig": { "BaseliningJobName": "string", "ConstraintsResource": { "S3Uri": "string"
} },
"ModelExplainabilityJobInput": { "EndpointInput": {
"ProbabilityAttribute": "string", "ProbabilityThresholdAttribute": number, "S3DataDistributionType": "string", "S3InputMode": "string",
"StartTimeOffset": "string"
} },
"ModelExplainabilityJobOutputConfig": { "KmsKeyId": "string",
"EnableInterContainerTrafficEncryption": boolean, "EnableNetworkIsolation": boolean,
"VpcConfig": {
"SecurityGroupIds": [ "string" ], "Subnets": [ "string" ]
}
CreateModelExplainabilityJobDefinition
},
"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 (p. 1463).
The request accepts the following data in JSON format.
JobDefinitionName (p. 121)
The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS 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 (p. 121)
Identifies the resources to deploy for a monitoring job.
Type: MonitoringResources (p. 1204) object Required: Yes
ModelExplainabilityAppSpecification (p. 121)
Configures the model explainability job to run a specified Docker container image.
Type: ModelExplainabilityAppSpecification (p. 1153) object Required: Yes
ModelExplainabilityBaselineConfig (p. 121)
The baseline configuration for a model explainability job.
Type: ModelExplainabilityBaselineConfig (p. 1154) object Required: No
ModelExplainabilityJobInput (p. 121) Inputs for the model explainability job.
Type: ModelExplainabilityJobInput (p. 1155) object Required: Yes
CreateModelExplainabilityJobDefinition
ModelExplainabilityJobOutputConfig (p. 121) The output configuration for monitoring jobs.
Type: MonitoringOutputConfig (p. 1203) object Required: Yes
NetworkConfig (p. 121)
Networking options for a model explainability job.
Type: MonitoringNetworkConfig (p. 1201) object Required: No
RoleArn (p. 121)
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 (p. 121)
A time limit for how long the monitoring job is allowed to run before stopping.
Type: MonitoringStoppingCondition (p. 1213) object Required: No
Tags (p. 121)
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
Type: Array of Tag (p. 1370) 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 (p. 123)
The Amazon Resource Name (ARN) of the model explainability job.
CreateModelExplainabilityJobDefinition
Type: String
Length Constraints: Maximum length of 256.
Pattern: .*
Errors
For information about the errors that are common to all actions, see Common Errors (p. 1465).
ResourceInUse
Resource being accessed is in use.
HTTP Status Code: 400 ResourceLimitExceeded
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 AWS SDKs, see the following:
• AWS Command Line Interface
• AWS SDK for .NET
• AWS SDK for C++
• AWS SDK for Go
• AWS SDK for Java V2
• AWS SDK for JavaScript
• AWS SDK for PHP V3
• AWS SDK for Python
• AWS SDK for Ruby V3
CreateModelPackage
CreateModelPackage
Service: Amazon SageMaker Service
Creates a model package that you can use to create SageMaker models or list on AWS Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on AWS Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in AWS Marketplace, provide a value for SourceAlgorithmSpecification.
Note
There are two types of model packages:
• Versioned - a model that is part of a model group in the model registry.
• Unversioned - a model package that is not part of a model group.
Request Syntax
{ "AdditionalInferenceSpecifications": [ {
"SupportedRealtimeInferenceInstanceTypes": [ "string" ], "SupportedResponseMIMETypes": [ "string" ],
"SupportedTransformInstanceTypes": [ "string" ] }
],
"CertifyForMarketplace": boolean, "ClientToken": "string",
"CustomerMetadataProperties": { "string" : "string"
},
"Domain": "string", "DriftCheckBaselines": { "Bias": {
"ConfigFile": {
"ContentDigest": "string", "ContentType": "string",
CreateModelPackage
"InferenceSpecification": { "Containers": [
CreateModelPackage
"ProductId": "string"
} ],
"SupportedContentTypes": [ "string" ],
"SupportedRealtimeInferenceInstanceTypes": [ "string" ], "SupportedResponseMIMETypes": [ "string" ],
"SupportedTransformInstanceTypes": [ "string" ] },
"MetadataProperties": { "CommitId": "string", "GeneratedBy": "string", "ProjectId": "string", "Repository": "string"
},
"ModelApprovalStatus": "string", "ModelMetrics": {
"ModelPackageDescription": "string",
CreateModelPackage
"ModelPackageGroupName": "string", "ModelPackageName": "string", "SamplePayloadUrl": "string", "SourceAlgorithmSpecification": { "SourceAlgorithms": [
"Task": "string",
"ValidationSpecification": { "ValidationProfiles": [
"ValidationRole": "string"
} }
Request Parameters
For information about the parameters that are common to all actions, see Common Parameters (p. 1463).
The request accepts the following data in JSON format.
CreateModelPackage
AdditionalInferenceSpecifications (p. 125)
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.
Type: Array of AdditionalInferenceSpecificationDefinition (p. 862) objects Array Members: Minimum number of 1 item. Maximum number of 15 items.
Required: No
CertifyForMarketplace (p. 125)
Whether to certify the model package for listing on AWS Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
Type: Boolean Required: No ClientToken (p. 125)
A unique token that guarantees that the call to this API is idempotent.
Type: String
Length Constraints: Minimum length of 1. Maximum length of 36.
Pattern: ^[a-zA-Z0-9-]+$
Required: No
CustomerMetadataProperties (p. 125)
The metadata properties associated with the model package versions.
Type: String to string map
Map Entries: Maximum number of 50 items.
Key Length Constraints: Minimum length of 1. Maximum length of 128.
Key Pattern: ^([\p{L}\p{Z}\p{N}_.:\/=+\-@]*)${1,128}
Value Length Constraints: Minimum length of 1. Maximum length of 256.
Value Pattern: ^([\p{L}\p{Z}\p{N}_.:\/=+\-@]*)${1,256}
Required: No Domain (p. 125)
The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
Type: String Required: No
DriftCheckBaselines (p. 125)
Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
CreateModelPackage
Type: DriftCheckBaselines (p. 993) object Required: No
InferenceSpecification (p. 125)
Specifies details about inference jobs that can be run with models based on this model package, including the following:
• The Amazon ECR paths of containers that contain the inference code and model artifacts.
• The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
• The input and output content formats that the model package supports for inference.
Type: InferenceSpecification (p. 1100) object Required: No
MetadataProperties (p. 125)
Metadata properties of the tracking entity, trial, or trial component.
Type: MetadataProperties (p. 1137) object Required: No
ModelApprovalStatus (p. 125)
Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved to deploy the model.
Type: String
Valid Values: Approved | Rejected | PendingManualApproval Required: No
ModelMetrics (p. 125)
A structure that contains model metrics reports.
Type: ModelMetrics (p. 1161) object Required: No
ModelPackageDescription (p. 125) A description of the model package.
Type: String
Length Constraints: Maximum length of 1024.
Pattern: [\p{L}\p{M}\p{Z}\p{S}\p{N}\p{P}]*
Required: No
ModelPackageGroupName (p. 125)
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
CreateModelPackage
Type: String
Length Constraints: Minimum length of 1. Maximum length of 170.
Pattern: (arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:[a-z\-]*\/)?([a-zA-Z0-9]([a-zA-Z0-9-]){0,62})(?<!-)$
Required: No
ModelPackageName (p. 125)
The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
Type: String
Length Constraints: Minimum length of 1. Maximum length of 63.
Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}$
Required: No
SamplePayloadUrl (p. 125)
The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
Type: String
Length Constraints: Maximum length of 1024.
Pattern: ^(https|s3)://([^/]+)/?(.*)$
Required: No
SourceAlgorithmSpecification (p. 125)
Details about the algorithm that was used to create the model package.
Type: SourceAlgorithmSpecification (p. 1361) object Required: No
Tags (p. 125)
A list of key value pairs associated with the model. For more information, see Tagging AWS resources in the AWS General Reference Guide.
Type: Array of Tag (p. 1370) objects
Array Members: Minimum number of 0 items. Maximum number of 50 items.
Required: No Task (p. 125)
The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
Type: String Required: No
CreateModelPackage
ValidationSpecification (p. 125)
Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
Type: ModelPackageValidationSpecification (p. 1179) object Required: No
Response Syntax
{ "ModelPackageArn": "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.
ModelPackageArn (p. 132)
The Amazon Resource Name (ARN) of the new model package.
Type: String
Length Constraints: Minimum length of 1. Maximum length of 2048.
Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:model-package/.*
Errors
For information about the errors that are common to all actions, see Common Errors (p. 1465).
ConflictException
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
HTTP Status Code: 400 ResourceLimitExceeded
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 AWS SDKs, see the following:
• AWS Command Line Interface
• AWS SDK for .NET
• AWS SDK for C++
CreateModelPackage
• AWS SDK for Go
• AWS SDK for Java V2
• AWS SDK for JavaScript
• AWS SDK for PHP V3
• AWS SDK for Python
• AWS SDK for Ruby V3
CreateModelPackageGroup
CreateModelPackageGroup
Service: Amazon SageMaker Service
Creates a model group. A model group contains a group of model versions.
Request Syntax
{
"ModelPackageGroupDescription": "string", "ModelPackageGroupName": "string", "Tags": [
{
"Key": "string", "Value": "string"
} ] }
Request Parameters
For information about the parameters that are common to all actions, see Common Parameters (p. 1463).
The request accepts the following data in JSON format.
ModelPackageGroupDescription (p. 134) A description for the model group.
Type: String
Length Constraints: Maximum length of 1024.
Pattern: [\p{L}\p{M}\p{Z}\p{S}\p{N}\p{P}]*
Required: No
ModelPackageGroupName (p. 134) The name of the model group.
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 Tags (p. 134)
A list of key value pairs associated with the model group. For more information, see Tagging AWS resources in the AWS General Reference Guide.
Type: Array of Tag (p. 1370) objects
Array Members: Minimum number of 0 items. Maximum number of 50 items.
Required: No
CreateModelPackageGroup
Response Syntax
{ "ModelPackageGroupArn": "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.
ModelPackageGroupArn (p. 135)
The Amazon Resource Name (ARN) of the model group.
Type: String
Length Constraints: Minimum length of 1. Maximum length of 2048.
Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:model-package-group/.*
Errors
For information about the errors that are common to all actions, see Common Errors (p. 1465).
ResourceLimitExceeded
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 AWS SDKs, see the following:
• AWS Command Line Interface
• AWS SDK for .NET
• AWS SDK for C++
• AWS SDK for Go
• AWS SDK for Java V2
• AWS SDK for JavaScript
• AWS SDK for PHP V3
• AWS SDK for Python
• AWS SDK for Ruby V3