class_docstr: Base class of Amazon SageMaker Explainability API model monitors.
  
  This class is an ``abstract base class``, please instantiate its subclasses
  if you want to monitor bias metrics or feature attribution of an endpoint.
class_docstr_tok: ["Base","class","of","Amazon","SageMaker","Explainability","API","model","monitors",".","This","class","is","an","``","abstract","base","class","``",",","please","instantiate","its","subclasses","if","you","want","to","monitor","bias","metrics","or","feature","attribution","of","an","endpoint","."]
docstr: Initializes a monitor instance.
  
  The monitor handles baselining datasets and creating Amazon SageMaker
  Monitoring Schedules to monitor SageMaker endpoints.
  
  Args:
      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.
      instance_type (str): Type of EC2 instance to use for
          the job, for example, '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 job's volume.
      output_kms_key (str): The KMS key id for the job's outputs.
      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
      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.
      sagemaker_session (sagemaker.session.Session): Session object which
          manages interactions with Amazon SageMaker APIs and any other
          AWS services needed. If not specified, one is created using
          the default AWS configuration chain.
      env (dict): Environment variables to be passed to the job.
      tags (Optional[Tags]): List of tags to be passed to the job.
      network_config (sagemaker.network.NetworkConfig): A NetworkConfig
          object that configures network isolation, encryption of
          inter-container traffic, security group IDs, and subnets.
code: def __init__(
      self,
      role=None,
      instance_count=1,
      instance_type="ml.m5.xlarge",
      volume_size_in_gb=30,
      volume_kms_key=None,
      output_kms_key=None,
      max_runtime_in_seconds=None,
      base_job_name=None,
      sagemaker_session=None,
      env=None,
      tags=None,
      network_config=None,
  ):
      """Initializes a monitor instance.
  
      The monitor handles baselining datasets and creating Amazon SageMaker
      Monitoring Schedules to monitor SageMaker endpoints.
  
      Args:
          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.
          instance_type (str): Type of EC2 instance to use for
              the job, for example, '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 job's volume.
          output_kms_key (str): The KMS key id for the job's outputs.
          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
          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.
          sagemaker_session (sagemaker.session.Session): Session object which
              manages interactions with Amazon SageMaker APIs and any other
              AWS services needed. If not specified, one is created using
              the default AWS configuration chain.
          env (dict): Environment variables to be passed to the job.
          tags (Optional[Tags]): List of tags to be passed to the job.
          network_config (sagemaker.network.NetworkConfig): A NetworkConfig
              object that configures network isolation, encryption of
              inter-container traffic, security group IDs, and subnets.
      """
      if (
          type(self) == __class__
      ):  # pylint: disable=unidiomatic-typecheck
          raise TypeError(
              "{} is abstract, please instantiate its subclasses instead.".format(
                  __class__.__name__
              )
          )
  
      session = sagemaker_session or Session()
      clarify_image_uri = image_uris.retrieve(
          "clarify", session.boto_session.region_name
      )
  
      super(ClarifyModelMonitor, self).__init__(
          role=role,
          image_uri=clarify_image_uri,
          instance_count=instance_count,
          instance_type=instance_type,
          volume_size_in_gb=volume_size_in_gb,
          volume_kms_key=volume_kms_key,
          output_kms_key=output_kms_key,
          max_runtime_in_seconds=max_runtime_in_seconds,
          base_job_name=base_job_name,
          sagemaker_session=session,
          env=env,
          tags=format_tags(tags),
          network_config=network_config,
      )
      self.latest_baselining_job_config = None
  
imports: from __future__ import print_function, absolute_import
  import copy
  import json
  import logging
  import uuid
  from sagemaker.model_monitor import model_monitoring
  from sagemaker import image_uris, s3
  from sagemaker.session import Session
  from sagemaker.utils import name_from_base, format_tags
  from sagemaker.clarify import SageMakerClarifyProcessor, ModelPredictedLabelConfig
  from sagemaker.lineage._utils import get_resource_name_from_arn
label_desc: Use image node_id 1 to create a new ClarifyModelMonitor object from inherited base classes: mm with example: obj = ClarifyModelMonitor(role, instance_count, instance_type, volume_size_in_gb, volume_kms_key, output_kms_key, max_runtime_in_seconds, base_job_name, sagemaker_session, env, tags, network_config)