code: def test_default_model_monitor_suggest_baseline_with_linfinity_categorical_drift_method(
      processor_init, sagemaker_session
  ):
      my_default_monitor = DefaultModelMonitor(
          role=ROLE,
          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=sagemaker_session,
          env=ENVIRONMENT,
          tags=TAGS,
          network_config=NETWORK_CONFIG,
      )
      distribution_constraints_with_linfinity_categorical_drift_method = DataQualityDistributionConstraints(
          categorical_drift_method=LINFINITY_METHOD
      )
      monitoring_config_with_linfinity_categorical_drift_method = DataQualityMonitoringConfig(
          distribution_constraints=distribution_constraints_with_linfinity_categorical_drift_method
      )
      processor_init.return_value = Mock()
      my_default_monitor.suggest_baseline(
          baseline_dataset=BASELINE_DATASET_PATH,
          dataset_format=DatasetFormat.csv(header=False),
          record_preprocessor_script=PREPROCESSOR_PATH,
          post_analytics_processor_script=POSTPROCESSOR_PATH,
          output_s3_uri=OUTPUT_S3_URI,
          wait=False,
          logs=False,
          monitoring_config_override=monitoring_config_with_linfinity_categorical_drift_method,
      )
  
      assert my_default_monitor.role == ROLE
      assert my_default_monitor.instance_count == INSTANCE_COUNT
      assert my_default_monitor.instance_type == INSTANCE_TYPE
      assert my_default_monitor.volume_size_in_gb == VOLUME_SIZE_IN_GB
      assert my_default_monitor.volume_kms_key == VOLUME_KMS_KEY
      assert my_default_monitor.output_kms_key == OUTPUT_KMS_KEY
      assert (
          my_default_monitor.max_runtime_in_seconds
          == MAX_RUNTIME_IN_SECONDS
      )
      assert my_default_monitor.base_job_name == BASE_JOB_NAME
      assert my_default_monitor.sagemaker_session == sagemaker_session
      assert my_default_monitor.tags == TAGS
      assert my_default_monitor.network_config == NETWORK_CONFIG
      assert my_default_monitor.image_uri == DEFAULT_IMAGE_URI
      assert (
          BASE_JOB_NAME in my_default_monitor.latest_baselining_job_name
      )
      assert (
          my_default_monitor.latest_baselining_job_name != BASE_JOB_NAME
      )
      assert my_default_monitor.env[ENV_KEY_1] == ENV_VALUE_1
  
      assert (
          processor_init.call_args.kwargs["env"][
              _CATEGORICAL_DRIFT_METHOD_ENV_NAME
          ]
          == LINFINITY_METHOD
      )
  
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 7 for calling a global function with example usage: test_default_model_monitor_suggest_baseline_with_linfinity_categorical_drift_method(processor_init, sagemaker_session) without return types