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: Get the processing job logs for the most recent monitoring execution
  
  Args:
      wait (bool): Whether the call should wait until the job completes (default: False).
  
  Raises:
      ValueError: If no execution job or processing job for the last execution has run
  
  Returns: None
code: def get_latest_execution_logs(self, wait=False):
      """Get the processing job logs for the most recent monitoring execution
  
      Args:
          wait (bool): Whether the call should wait until the job completes (default: False).
  
      Raises:
          ValueError: If no execution job or processing job for the last execution has run
  
      Returns: None
      """
      monitoring_executions = (
          self.sagemaker_session.list_monitoring_executions(
              monitoring_schedule_name=self.monitoring_schedule_name
          )
      )
      if (
          len(monitoring_executions["MonitoringExecutionSummaries"])
          == 0
      ):
          raise ValueError("No execution jobs were kicked off.")
      if (
          "ProcessingJobArn"
          not in monitoring_executions["MonitoringExecutionSummaries"][
              0
          ]
      ):
          raise ValueError(
              "Processing Job did not run for the last execution"
          )
      job_arn = monitoring_executions["MonitoringExecutionSummaries"][
          0
      ]["ProcessingJobArn"]
      self.sagemaker_session.logs_for_processing_job(
          job_name=get_resource_name_from_arn(job_arn), wait=wait
      )
  
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 5 for calling the ClarifyModelMonitor obj's underlying member method code with example usage: obj.get_latest_execution_logs(wait) without return types