CfnModelExplainabilityJobDefinitionMixinProps

class aws_cdk.mixins_preview.aws_sagemaker.mixins.CfnModelExplainabilityJobDefinitionMixinProps(*, endpoint_name=None, job_definition_name=None, job_resources=None, model_explainability_app_specification=None, model_explainability_baseline_config=None, model_explainability_job_input=None, model_explainability_job_output_config=None, network_config=None, role_arn=None, stopping_condition=None, tags=None)

Bases: object

Properties for CfnModelExplainabilityJobDefinitionPropsMixin.

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 model explainability job definition. The name must be unique within an AWS Region in the AWS account.

  • job_resources (Union[IResolvable, MonitoringResourcesProperty, Dict[str, Any], None]) – Identifies the resources to deploy for a monitoring job.

  • model_explainability_app_specification (Union[IResolvable, ModelExplainabilityAppSpecificationProperty, Dict[str, Any], None]) – Configures the model explainability job to run a specified Docker container image.

  • model_explainability_baseline_config (Union[IResolvable, ModelExplainabilityBaselineConfigProperty, Dict[str, Any], None]) – The baseline configuration for a model explainability job.

  • model_explainability_job_input (Union[IResolvable, ModelExplainabilityJobInputProperty, Dict[str, Any], None]) – Inputs for the model explainability job.

  • model_explainability_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]) – Networking options for a model explainability 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:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html

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_explainability_job_definition_mixin_props = sagemaker_mixins.CfnModelExplainabilityJobDefinitionMixinProps(
    endpoint_name="endpointName",
    job_definition_name="jobDefinitionName",
    job_resources=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.MonitoringResourcesProperty(
        cluster_config=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.ClusterConfigProperty(
            instance_count=123,
            instance_type="instanceType",
            volume_kms_key_id="volumeKmsKeyId",
            volume_size_in_gb=123
        )
    ),
    model_explainability_app_specification=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.ModelExplainabilityAppSpecificationProperty(
        config_uri="configUri",
        environment={
            "environment_key": "environment"
        },
        image_uri="imageUri"
    ),
    model_explainability_baseline_config=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.ModelExplainabilityBaselineConfigProperty(
        baselining_job_name="baseliningJobName",
        constraints_resource=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.ConstraintsResourceProperty(
            s3_uri="s3Uri"
        )
    ),
    model_explainability_job_input=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.ModelExplainabilityJobInputProperty(
        batch_transform_input=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.BatchTransformInputProperty(
            data_captured_destination_s3_uri="dataCapturedDestinationS3Uri",
            dataset_format=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.DatasetFormatProperty(
                csv=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.CsvProperty(
                    header=False
                ),
                json=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.JsonProperty(
                    line=False
                ),
                parquet=False
            ),
            features_attribute="featuresAttribute",
            inference_attribute="inferenceAttribute",
            local_path="localPath",
            probability_attribute="probabilityAttribute",
            s3_data_distribution_type="s3DataDistributionType",
            s3_input_mode="s3InputMode"
        ),
        endpoint_input=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.EndpointInputProperty(
            endpoint_name="endpointName",
            features_attribute="featuresAttribute",
            inference_attribute="inferenceAttribute",
            local_path="localPath",
            probability_attribute="probabilityAttribute",
            s3_data_distribution_type="s3DataDistributionType",
            s3_input_mode="s3InputMode"
        )
    ),
    model_explainability_job_output_config=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.MonitoringOutputConfigProperty(
        kms_key_id="kmsKeyId",
        monitoring_outputs=[sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.MonitoringOutputProperty(
            s3_output=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.S3OutputProperty(
                local_path="localPath",
                s3_upload_mode="s3UploadMode",
                s3_uri="s3Uri"
            )
        )]
    ),
    network_config=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.NetworkConfigProperty(
        enable_inter_container_traffic_encryption=False,
        enable_network_isolation=False,
        vpc_config=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.VpcConfigProperty(
            security_group_ids=["securityGroupIds"],
            subnets=["subnets"]
        )
    ),
    role_arn="roleArn",
    stopping_condition=sagemaker_mixins.CfnModelExplainabilityJobDefinitionPropsMixin.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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-endpointname

job_definition_name

The name of the model explainability job definition.

The name must be unique within an AWS Region in the AWS account.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-jobdefinitionname

job_resources

Identifies the resources to deploy for a monitoring job.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-jobresources

model_explainability_app_specification

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

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-modelexplainabilityappspecification

model_explainability_baseline_config

The baseline configuration for a model explainability job.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-modelexplainabilitybaselineconfig

model_explainability_job_input

Inputs for the model explainability job.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-modelexplainabilityjobinput

model_explainability_job_output_config

The output configuration for monitoring jobs.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-modelexplainabilityjoboutputconfig

network_config

Networking options for a model explainability job.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-networkconfig

role_arn

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

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-rolearn

stopping_condition

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

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-stoppingcondition

tags

An array of key-value pairs to apply to this resource.

For more information, see Tag .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelexplainabilityjobdefinition.html#cfn-sagemaker-modelexplainabilityjobdefinition-tags