code: def test_stop(session, *args):
      job_settings = _JobSettings(
          image_uri=IMAGE,
          s3_root_uri=S3_URI,
          role=ROLE_ARN,
          instance_type="ml.m5.large",
      )
      job = _Job.start(
          job_settings,
          job_function,
          func_args=(1, 2),
          func_kwargs={"c": 3, "d": 4},
      )
  
      job.stop()
  
      session().sagemaker_client.stop_training_job.assert_called_once_with(
          TrainingJobName=job.job_name
      )
  
imports: from __future__ import absolute_import
  import os
  import sys
  import pytest
  from mock import patch, Mock, ANY, mock_open
  from mock.mock import MagicMock
  from sagemaker.config import load_sagemaker_config
  from sagemaker.remote_function.checkpoint_location import CheckpointLocation
  from sagemaker.remote_function.core.stored_function import _SerializedData
  from sagemaker.session_settings import SessionSettings
  from sagemaker.remote_function.spark_config import SparkConfig
  from sagemaker.remote_function.custom_file_filter import CustomFileFilter
  from sagemaker.remote_function.core.pipeline_variables import Context
  from sagemaker.workflow.pipeline_context import _PipelineConfig
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from sagemaker.workflow.execution_variables import ExecutionVariables
  from sagemaker.utils import sagemaker_timestamp
  from tests.unit import DATA_DIR
  from sagemaker.remote_function.job import _JobSettings, _Job, _convert_run_to_json, _prepare_and_upload_runtime_scripts, _prepare_and_upload_workspace, _prepare_and_upload_spark_dependent_files, _upload_spark_submit_deps, _upload_serialized_spark_configuration, _extend_spark_config_to_request, _prepare_dependencies_and_pre_execution_scripts
label_desc: Use image node_id 22 for calling a global function with example usage: test_stop(session) without return types