code: def s3_uri_prefix(sagemaker_session):
      # Note: not using unique_name_from_base() here because the config contents are expected to
      # change very rarely (if ever), so rather than writing new files and deleting them every time
      # we can just use the same S3 paths
      s3_uri_prefix = os.path.join(
          "s3://",
          sagemaker_session.default_bucket(),
          S3_KEY_PREFIX,
      )
      return s3_uri_prefix
  
imports: from __future__ import absolute_import
  import os
  import pathlib
  import tempfile
  import pytest
  import yaml
  from botocore.config import Config
  from sagemaker import PipelineModel, image_uris, Model, Predictor, Session
  from sagemaker.config import load_sagemaker_config
  from sagemaker.model_monitor import DataCaptureConfig
  from sagemaker.s3 import S3Uploader
  from sagemaker.sparkml import SparkMLModel
  from sagemaker.utils import sagemaker_timestamp
  from tests.integ import DATA_DIR
  from tests.integ.kms_utils import get_or_create_kms_key
  from tests.integ.test_inference_pipeline import SCHEMA
  from tests.integ.timeout import timeout_and_delete_endpoint_by_name
label_desc: Use image node_id 4 for calling a global function with example usage: s3_uri_prefix(sagemaker_session) and returns: s3_uri_prefix