code: def test_default_monitor_suggest_baseline_with_invalid_categorical_drift_method(
      sagemaker_session, output_kms_key, volume_kms_key
  ):
      baseline_dataset = os.path.join(
          DATA_DIR, "monitor/baseline_dataset.csv"
      )
  
      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,
          sagemaker_session=sagemaker_session,
          env=ENVIRONMENT,
          tags=TAGS,
          network_config=NETWORK_CONFIG,
      )
  
      output_s3_uri = os.path.join(
          "s3://",
          sagemaker_session.default_bucket(),
          INTEG_TEST_MONITORING_OUTPUT_BUCKET,
          str(uuid.uuid4()),
      )
  
      distribution_constraints_with_invalid_categorical_drift_method = DataQualityDistributionConstraints(
          categorical_drift_method="INVALID_CATEGORICAL_DRIFT_METHOD"
      )
      monitoring_config_with_invalid_categorical_drift_method = DataQualityMonitoringConfig(
          distribution_constraints=distribution_constraints_with_invalid_categorical_drift_method
      )
  
      with pytest.raises(RuntimeError) as error:
          my_default_monitor.suggest_baseline(
              baseline_dataset=baseline_dataset,
              dataset_format=DatasetFormat.csv(header=False),
              output_s3_uri=output_s3_uri,
              wait=True,
              logs=False,
              monitoring_config_override=monitoring_config_with_invalid_categorical_drift_method,
          )
      assert "Invalid value for monitoring_config_override." in str(
          error
      )
  
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 13 for calling a global function with example usage: test_default_monitor_suggest_baseline_with_invalid_categorical_drift_method(sagemaker_session, output_kms_key, volume_kms_key) without return types