code: def test_sklearn(
      sagemaker_session, sklearn_latest_version, cpu_instance_type
  ):
      script_path = os.path.join(DATA_DIR, "dummy_script.py")
      input_file_path = os.path.join(DATA_DIR, "dummy_input.txt")
  
      sklearn_processor = SKLearnProcessor(
          framework_version=sklearn_latest_version,
          role=ROLE,
          instance_type=cpu_instance_type,
          instance_count=1,
          command=["python3"],
          sagemaker_session=sagemaker_session,
          base_job_name="test-sklearn",
      )
  
      sklearn_processor.run(
          code=script_path,
          inputs=[
              ProcessingInput(
                  source=input_file_path,
                  destination="/opt/ml/processing/inputs/",
              )
          ],
          wait=False,
          logs=False,
      )
  
      job_description = sklearn_processor.latest_job.describe()
  
      assert len(job_description["ProcessingInputs"]) == 2
      assert (
          job_description["ProcessingResources"]["ClusterConfig"][
              "InstanceCount"
          ]
          == 1
      )
      assert (
          job_description["ProcessingResources"]["ClusterConfig"][
              "InstanceType"
          ]
          == cpu_instance_type
      )
      assert (
          job_description["ProcessingResources"]["ClusterConfig"][
              "VolumeSizeInGB"
          ]
          == 30
      )
      assert job_description["StoppingCondition"] == {
          "MaxRuntimeInSeconds": 86400
      }
      assert job_description["AppSpecification"][
          "ContainerEntrypoint"
      ] == [
          "python3",
          "/opt/ml/processing/input/code/dummy_script.py",
      ]
      assert ROLE in job_description["RoleArn"]
  
imports: from __future__ import absolute_import
  import os
  import pytest
  from botocore.config import Config
  from sagemaker import image_uris, Session
  from sagemaker.dataset_definition.inputs import DatasetDefinition, RedshiftDatasetDefinition, AthenaDatasetDefinition, S3Input
  from sagemaker.network import NetworkConfig
  from sagemaker.processing import ProcessingInput, ProcessingOutput, ScriptProcessor, Processor, ProcessingJob, FeatureStoreOutput
  from sagemaker.sklearn.processing import SKLearnProcessor
  from tests.integ import DATA_DIR
  from tests.integ.kms_utils import get_or_create_kms_key
label_desc: Use image node_id 6 for calling a global function with example usage: test_sklearn(sagemaker_session, sklearn_latest_version, cpu_instance_type) without return types