CfnModelExplainabilityJobDefinitionProps¶
-
class
aws_cdk.aws_sagemaker.
CfnModelExplainabilityJobDefinitionProps
(*, job_resources, model_explainability_app_specification, model_explainability_job_input, model_explainability_job_output_config, role_arn, job_definition_name=None, model_explainability_baseline_config=None, network_config=None, stopping_condition=None, tags=None)¶ Bases:
object
Properties for defining a
CfnModelExplainabilityJobDefinition
.- Parameters
job_resources (
Union
[IResolvable
,MonitoringResourcesProperty
]) – Identifies the resources to deploy for a monitoring job.model_explainability_app_specification (
Union
[IResolvable
,ModelExplainabilityAppSpecificationProperty
]) – Configures the model explainability job to run a specified Docker container image.model_explainability_job_input (
Union
[IResolvable
,ModelExplainabilityJobInputProperty
]) – Inputs for the model explainability job.model_explainability_job_output_config (
Union
[IResolvable
,MonitoringOutputConfigProperty
]) – The output configuration for monitoring jobs.role_arn (
str
) – The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.job_definition_name (
Optional
[str
]) – The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.model_explainability_baseline_config (
Union
[IResolvable
,ModelExplainabilityBaselineConfigProperty
,None
]) – The baseline configuration for a model explainability job.network_config (
Union
[IResolvable
,NetworkConfigProperty
,None
]) – Networking options for a model explainability job.stopping_condition (
Union
[IResolvable
,StoppingConditionProperty
,None
]) –AWS::SageMaker::ModelExplainabilityJobDefinition.StoppingCondition
.tags (
Optional
[Sequence
[CfnTag
]]) – An array of key-value pairs to apply to this resource. For more information, see Tag .
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_sagemaker as sagemaker cfn_model_explainability_job_definition_props = sagemaker.CfnModelExplainabilityJobDefinitionProps( job_resources=sagemaker.CfnModelExplainabilityJobDefinition.MonitoringResourcesProperty( cluster_config=sagemaker.CfnModelExplainabilityJobDefinition.ClusterConfigProperty( instance_count=123, instance_type="instanceType", volume_size_in_gb=123, # the properties below are optional volume_kms_key_id="volumeKmsKeyId" ) ), model_explainability_app_specification=sagemaker.CfnModelExplainabilityJobDefinition.ModelExplainabilityAppSpecificationProperty( config_uri="configUri", image_uri="imageUri", # the properties below are optional environment={ "environment_key": "environment" } ), model_explainability_job_input=sagemaker.CfnModelExplainabilityJobDefinition.ModelExplainabilityJobInputProperty( endpoint_input=sagemaker.CfnModelExplainabilityJobDefinition.EndpointInputProperty( endpoint_name="endpointName", local_path="localPath", # the properties below are optional features_attribute="featuresAttribute", inference_attribute="inferenceAttribute", probability_attribute="probabilityAttribute", s3_data_distribution_type="s3DataDistributionType", s3_input_mode="s3InputMode" ) ), model_explainability_job_output_config=sagemaker.CfnModelExplainabilityJobDefinition.MonitoringOutputConfigProperty( monitoring_outputs=[sagemaker.CfnModelExplainabilityJobDefinition.MonitoringOutputProperty( s3_output=sagemaker.CfnModelExplainabilityJobDefinition.S3OutputProperty( local_path="localPath", s3_uri="s3Uri", # the properties below are optional s3_upload_mode="s3UploadMode" ) )], # the properties below are optional kms_key_id="kmsKeyId" ), role_arn="roleArn", # the properties below are optional job_definition_name="jobDefinitionName", model_explainability_baseline_config=sagemaker.CfnModelExplainabilityJobDefinition.ModelExplainabilityBaselineConfigProperty( baselining_job_name="baseliningJobName", constraints_resource=sagemaker.CfnModelExplainabilityJobDefinition.ConstraintsResourceProperty( s3_uri="s3Uri" ) ), network_config=sagemaker.CfnModelExplainabilityJobDefinition.NetworkConfigProperty( enable_inter_container_traffic_encryption=False, enable_network_isolation=False, vpc_config=sagemaker.CfnModelExplainabilityJobDefinition.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] ) ), stopping_condition=sagemaker.CfnModelExplainabilityJobDefinition.StoppingConditionProperty( max_runtime_in_seconds=123 ), tags=[CfnTag( key="key", value="value" )] )
Attributes
-
job_definition_name
¶ The name of the model explainability job definition.
The name must be unique within an AWS Region in the AWS account.
-
job_resources
¶ Identifies the resources to deploy for a monitoring job.
-
model_explainability_app_specification
¶ Configures the model explainability job to run a specified Docker container image.
-
model_explainability_baseline_config
¶ The baseline configuration for a model explainability job.
-
model_explainability_job_input
¶ Inputs for the model explainability job.
-
model_explainability_job_output_config
¶ The output configuration for monitoring jobs.
-
network_config
¶ Networking options for a model explainability job.
-
role_arn
¶ The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
-
stopping_condition
¶ AWS::SageMaker::ModelExplainabilityJobDefinition.StoppingCondition
.
An array of key-value pairs to apply to this resource.
For more information, see Tag .