CfnModelQualityJobDefinitionMixinProps
- class aws_cdk.mixins_preview.aws_sagemaker.mixins.CfnModelQualityJobDefinitionMixinProps(*, endpoint_name=None, job_definition_name=None, job_resources=None, model_quality_app_specification=None, model_quality_baseline_config=None, model_quality_job_input=None, model_quality_job_output_config=None, network_config=None, role_arn=None, stopping_condition=None, tags=None)
Bases:
objectProperties for CfnModelQualityJobDefinitionPropsMixin.
- Parameters:
endpoint_name (
Optional[str]) – The name of the endpoint used to run the monitoring job.job_definition_name (
Optional[str]) – The name of the monitoring job definition.job_resources (
Union[IResolvable,MonitoringResourcesProperty,Dict[str,Any],None]) – Identifies the resources to deploy for a monitoring job.model_quality_app_specification (
Union[IResolvable,ModelQualityAppSpecificationProperty,Dict[str,Any],None]) – Container image configuration object for the monitoring job.model_quality_baseline_config (
Union[IResolvable,ModelQualityBaselineConfigProperty,Dict[str,Any],None]) – Specifies the constraints and baselines for the monitoring job.model_quality_job_input (
Union[IResolvable,ModelQualityJobInputProperty,Dict[str,Any],None]) – A list of the inputs that are monitored. Currently endpoints are supported.model_quality_job_output_config (
Union[IResolvable,MonitoringOutputConfigProperty,Dict[str,Any],None]) – The output configuration for monitoring jobs.network_config (
Union[IResolvable,NetworkConfigProperty,Dict[str,Any],None]) – Specifies the network configuration for the monitoring job.role_arn (
Optional[str]) – The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.stopping_condition (
Union[IResolvable,StoppingConditionProperty,Dict[str,Any],None]) – A time limit for how long the monitoring job is allowed to run before stopping.tags (
Optional[Sequence[Union[CfnTag,Dict[str,Any]]]]) – An array of key-value pairs to apply to this resource. For more information, see Tag .
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk.mixins_preview.aws_sagemaker import mixins as sagemaker_mixins cfn_model_quality_job_definition_mixin_props = sagemaker_mixins.CfnModelQualityJobDefinitionMixinProps( endpoint_name="endpointName", job_definition_name="jobDefinitionName", job_resources=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.MonitoringResourcesProperty( cluster_config=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.ClusterConfigProperty( instance_count=123, instance_type="instanceType", volume_kms_key_id="volumeKmsKeyId", volume_size_in_gb=123 ) ), model_quality_app_specification=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.ModelQualityAppSpecificationProperty( container_arguments=["containerArguments"], container_entrypoint=["containerEntrypoint"], environment={ "environment_key": "environment" }, image_uri="imageUri", post_analytics_processor_source_uri="postAnalyticsProcessorSourceUri", problem_type="problemType", record_preprocessor_source_uri="recordPreprocessorSourceUri" ), model_quality_baseline_config=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.ModelQualityBaselineConfigProperty( baselining_job_name="baseliningJobName", constraints_resource=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.ConstraintsResourceProperty( s3_uri="s3Uri" ) ), model_quality_job_input=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.ModelQualityJobInputProperty( batch_transform_input=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.BatchTransformInputProperty( data_captured_destination_s3_uri="dataCapturedDestinationS3Uri", dataset_format=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.DatasetFormatProperty( csv=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.CsvProperty( header=False ), json=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.JsonProperty( line=False ), parquet=False ), end_time_offset="endTimeOffset", inference_attribute="inferenceAttribute", local_path="localPath", probability_attribute="probabilityAttribute", probability_threshold_attribute=123, s3_data_distribution_type="s3DataDistributionType", s3_input_mode="s3InputMode", start_time_offset="startTimeOffset" ), endpoint_input=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.EndpointInputProperty( endpoint_name="endpointName", end_time_offset="endTimeOffset", inference_attribute="inferenceAttribute", local_path="localPath", probability_attribute="probabilityAttribute", probability_threshold_attribute=123, s3_data_distribution_type="s3DataDistributionType", s3_input_mode="s3InputMode", start_time_offset="startTimeOffset" ), ground_truth_s3_input=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.MonitoringGroundTruthS3InputProperty( s3_uri="s3Uri" ) ), model_quality_job_output_config=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.MonitoringOutputConfigProperty( kms_key_id="kmsKeyId", monitoring_outputs=[sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.MonitoringOutputProperty( s3_output=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.S3OutputProperty( local_path="localPath", s3_upload_mode="s3UploadMode", s3_uri="s3Uri" ) )] ), network_config=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.NetworkConfigProperty( enable_inter_container_traffic_encryption=False, enable_network_isolation=False, vpc_config=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] ) ), role_arn="roleArn", stopping_condition=sagemaker_mixins.CfnModelQualityJobDefinitionPropsMixin.StoppingConditionProperty( max_runtime_in_seconds=123 ), tags=[CfnTag( key="key", value="value" )] )
Attributes
- endpoint_name
The name of the endpoint used to run the monitoring job.
- job_definition_name
The name of the monitoring job definition.
- job_resources
Identifies the resources to deploy for a monitoring job.
- model_quality_app_specification
Container image configuration object for the monitoring job.
- model_quality_baseline_config
Specifies the constraints and baselines for the monitoring job.
- model_quality_job_input
A list of the inputs that are monitored.
Currently endpoints are supported.
- model_quality_job_output_config
The output configuration for monitoring jobs.
- network_config
Specifies the network configuration for the monitoring 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
A time limit for how long the monitoring job is allowed to run before stopping.