code: def test_default_monitor_display_logs_errors(sagemaker_session):
      my_default_monitor = DefaultModelMonitor(
          role=ROLE, sagemaker_session=sagemaker_session
      )
  
      data_captured_destination_s3_uri = os.path.join(
          "s3://",
          sagemaker_session.default_bucket(),
          "sagemaker-serving-batch-transform",
          str(uuid.uuid4()),
      )
  
      batch_transform_input = BatchTransformInput(
          data_captured_destination_s3_uri=data_captured_destination_s3_uri,
          destination="/opt/ml/processing/output",
          dataset_format=MonitoringDatasetFormat.csv(header=False),
      )
  
      my_default_monitor.create_monitoring_schedule(
          batch_transform_input=batch_transform_input,
          schedule_cron_expression=CronExpressionGenerator.hourly(),
      )
  
      _wait_for_schedule_changes_to_apply(monitor=my_default_monitor)
  
      try:
          my_default_monitor.get_latest_execution_logs(wait=False)
      except ValueError as ve:
          assert "No execution jobs were kicked off." in str(ve)
  
      my_default_monitor.stop_monitoring_schedule()
      my_default_monitor.delete_monitoring_schedule()
  
imports: from __future__ import absolute_import
  import json
  import os
  import uuid
  import time
  import pytest
  import tests.integ
  import tests.integ.timeout
  from sagemaker.s3 import S3Uploader
  from datetime import datetime, timedelta
  from tests.integ import DATA_DIR
  from sagemaker.model_monitor import DatasetFormat
  from sagemaker.model_monitor import MonitoringDatasetFormat
  from sagemaker.model_monitor import NetworkConfig, Statistics, Constraints
  from sagemaker.model_monitor import ModelMonitor
  from sagemaker.model_monitor import DefaultModelMonitor
  from sagemaker.model_monitor import MonitoringOutput
  from sagemaker.model_monitor import DataCaptureConfig
  from sagemaker.model_monitor import BatchTransformInput
  from sagemaker.model_monitor import DataQualityMonitoringConfig
  from sagemaker.model_monitor import DataQualityDistributionConstraints
  from sagemaker.model_monitor.data_capture_config import _MODEL_MONITOR_S3_PATH
  from sagemaker.model_monitor.data_capture_config import _DATA_CAPTURE_S3_PATH
  from sagemaker.model_monitor import CronExpressionGenerator
  from sagemaker.model_monitor.monitoring_alert import MonitoringAlertSummary
  from sagemaker.processing import ProcessingInput
  from sagemaker.processing import ProcessingOutput
  from sagemaker.tensorflow.model import TensorFlowModel
  from sagemaker.utils import unique_name_from_base
  from tests.integ.kms_utils import get_or_create_kms_key
  from tests.integ.retry import retries
label_desc: Use image node_id 10 for calling a global function with example usage: test_default_monitor_display_logs_errors(sagemaker_session) without return types