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: Create and return a SageMakerClarifyProcessor object which will run the baselining job.
  
  Returns:
      sagemaker.clarify.SageMakerClarifyProcessor object.
code: def _create_baselining_processor(self):
      """Create and return a SageMakerClarifyProcessor object which will run the baselining job.
  
      Returns:
          sagemaker.clarify.SageMakerClarifyProcessor object.
      """
  
      baselining_processor = SageMakerClarifyProcessor(
          role=self.role,
          instance_count=self.instance_count,
          instance_type=self.instance_type,
          volume_size_in_gb=self.volume_size_in_gb,
          volume_kms_key=self.volume_kms_key,
          output_kms_key=self.output_kms_key,
          max_runtime_in_seconds=self.max_runtime_in_seconds,
          sagemaker_session=self.sagemaker_session,
          env=self.env,
          tags=self.tags,
          network_config=self.network_config,
      )
      baselining_processor.image_uri = self.image_uri
      baselining_processor.base_job_name = self.base_job_name
      return baselining_processor
  
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 6 for calling the ClarifyModelMonitor obj's underlying member method code with example usage: obj._create_baselining_processor() and returns: baselining_processor