code: def bias_monitor(sagemaker_session):
      monitor = ModelBiasMonitor(
          role=ROLE,
          instance_count=INSTANCE_COUNT,
          instance_type=INSTANCE_TYPE,
          volume_size_in_gb=VOLUME_SIZE_IN_GB,
          max_runtime_in_seconds=MAX_RUNTIME_IN_SECONDS,
          sagemaker_session=sagemaker_session,
          tags=TEST_TAGS,
      )
      return monitor
  
imports: from __future__ import print_function, absolute_import
  from datetime import datetime, timedelta
  import json
  import numpy
  import os
  import pandas
  import pytest
  import tempfile
  import uuid
  import time
  import tests.integ
  import tests.integ.timeout
  from sagemaker import image_uris, utils
  from sagemaker.model_monitor import BiasAnalysisConfig, CronExpressionGenerator, DataCaptureConfig, EndpointInput, ExplainabilityAnalysisConfig, ModelBiasMonitor, ModelExplainabilityMonitor, BatchTransformInput, MonitoringDatasetFormat
  from sagemaker.s3 import S3Uploader
  from sagemaker.utils import unique_name_from_base
  from sagemaker.clarify import BiasConfig, DataConfig, ModelConfig, ModelPredictedLabelConfig, SHAPConfig
  from sagemaker.model import Model
  from tests.integ import DATA_DIR
  from tests.integ.retry import retries
label_desc: Use image node_id 10 for calling a global function with example usage: bias_monitor(sagemaker_session) and returns: monitor