code: def test_model_monitor_exclude_feature(
      sagemaker_session,
      model_monitor_arguments,
      endpoint_input=EndpointInput(
          endpoint_name=ENDPOINT_NAME,
          destination=ENDPOINT_INPUT_LOCAL_PATH,
          start_time_offset=START_TIME_OFFSET,
          end_time_offset=END_TIME_OFFSET,
          features_attribute=FEATURES_ATTRIBUTE,
          inference_attribute=INFERENCE_ATTRIBUTE,
          probability_attribute=PROBABILITY_ATTRIBUTE,
          probability_threshold_attribute=PROBABILITY_THRESHOLD_ATTRIBUTE,
          exclude_features_attribute=EXCLUDE_FEATURES_ATTRIBUTE,
      ),
  ):
      model_monitor_arguments.create_monitoring_schedule(
          monitor_schedule_name=SCHEDULE_NAME,
          schedule_cron_expression=CronExpressionGenerator.now(),
          endpoint_input=endpoint_input,
          output=MonitoringOutput(
              source="/opt/ml/processing/output",
              destination=OUTPUT_S3_URI,
          ),
          data_analysis_start_time=NEW_START_TIME_OFFSET,
          data_analysis_end_time=NEW_END_TIME_OFFSET,
      )
  
      sagemaker_session.create_monitoring_schedule.assert_called_with(
          monitoring_schedule_name=SCHEDULE_NAME,
          schedule_expression=CronExpressionGenerator.now(),
          statistics_s3_uri=None,
          constraints_s3_uri=None,
          monitoring_inputs=[
              MODEL_QUALITY_MONITOR_JOB_INPUT_WITH_EXCULDE_FEATURES
          ],
          monitoring_output_config=JOB_OUTPUT_CONFIG,
          instance_count=INSTANCE_COUNT,
          instance_type=INSTANCE_TYPE,
          volume_size_in_gb=VOLUME_SIZE_IN_GB,
          volume_kms_key=VOLUME_KMS_KEY,
          image_uri=DEFAULT_IMAGE_URI,
          entrypoint=None,
          arguments=None,
          record_preprocessor_source_uri=None,
          post_analytics_processor_source_uri=None,
          max_runtime_in_seconds=3,
          environment=ENVIRONMENT,
          network_config=NETWORK_CONFIG._to_request_dict(),
          role_arn=ROLE,
          tags=TAGS,
          data_analysis_start_time=NEW_START_TIME_OFFSET,
          data_analysis_end_time=NEW_END_TIME_OFFSET,
      )
  
imports: from __future__ import absolute_import
  import copy
  import time
  from typing import Union
  import sagemaker
  import pytest
  from mock import Mock, patch, MagicMock
  from sagemaker.model_monitor import ModelMonitor, Constraints, CronExpressionGenerator, DefaultModelMonitor, EndpointInput, BatchTransformInput, ModelQualityMonitor, Statistics, MonitoringOutput, DataQualityMonitoringConfig, DataQualityDistributionConstraints
  from sagemaker.model_monitor.monitoring_alert import MonitoringAlertSummary, MonitoringAlertHistorySummary, MonitoringAlertActions, ModelDashboardIndicatorAction
  from sagemaker.network import NetworkConfig
  from sagemaker.model_monitor.dataset_format import MonitoringDatasetFormat, DatasetFormat
  from tests.unit import SAGEMAKER_CONFIG_MONITORING_SCHEDULE
label_desc: Use image node_id 42 for calling a global function with example usage: test_model_monitor_exclude_feature(sagemaker_session, model_monitor_arguments, endpoint_input) without return types