CheckJobConfig: CheckJobConfig class

In DyfanJones/sagemaker-r-workflow: sagemaker pipeline and workflows

CheckJobConfig class

Description

Check job config for QualityCheckStep and ClarifyCheckStep

Methods

Public methods

• CheckJobConfig$new()

• CheckJobConfig$.generate_model_monitor()

• CheckJobConfig$format()

• CheckJobConfig$clone()

---

Method new()

Constructs a CheckJobConfig instance.

Usage

CheckJobConfig$new(
  role,
  instance_count = 1,
  instance_type = "ml.m5.xlarge",
  volume_size_in_gb = 30,
  volume_kms_key = NULL,
  output_kms_key = NULL,
  max_runtime_in_seconds = NULL,
  base_job_name = NULL,
  sagemaker_session = NULL,
  env = NULL,
  tags = NULL,
  network_config = NULL
)

Arguments

role

(str): An AWS IAM role. The Amazon SageMaker jobs use this role.

instance_count

(int): The number of instances to run the jobs with (default: 1).

instance_type

(str): Type of EC2 instance to use for the job (default: 'ml.m5.xlarge').

volume_size_in_gb

(int): Size in GB of the EBS volume to use for storing data during processing (default: 30).

volume_kms_key

(str): A KMS key for the processing volume (default: None).

output_kms_key

(str): The KMS key id for the job's outputs (default: None).

max_runtime_in_seconds

(int): Timeout in seconds. After this amount of time, Amazon SageMaker terminates the job regardless of its current status. Default: 3600 if not specified

base_job_name

(str): Prefix for the job name. If not specified, a default name is generated based on the training image name and current timestamp (default: None).

sagemaker_session

(sagemaker.session.Session): Session object which manages interactions with Amazon SageMaker APIs and any other AWS services needed (default: None). If not specified, one is created using the default AWS configuration chain.

env

(dict): Environment variables to be passed to the job (default: None).

tags

([dict]): List of tags to be passed to the job (default: None).

network_config

(sagemaker.network.NetworkConfig): A NetworkConfig object that configures network isolation, encryption of inter-container traffic, security group IDs, and subnets (default: None).

---

Method .generate_model_monitor()

Generates a ModelMonitor object Generates a ModelMonitor object with required config attributes for QualityCheckStep and ClarifyCheckStep

Usage

CheckJobConfig$.generate_model_monitor(mm_type)

Arguments

mm_type

(str): The subclass type of ModelMonitor object. A valid mm_type should be one of the following: "DefaultModelMonitor", "ModelQualityMonitor", "ModelBiasMonitor", "ModelExplainabilityMonitor"

Returns

sagemaker.model_monitor.ModelMonitor or None if the mm_type is not valid

---

Method format()

Format class

Usage

CheckJobConfig$format()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

CheckJobConfig$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-workflow documentation built on April 3, 2022, 11:28 p.m.