code: def test_processing_job_from_processing_arn(sagemaker_session):
      processing_job = ProcessingJob.from_processing_arn(
          sagemaker_session=sagemaker_session,
          processing_job_arn="arn:aws:sagemaker:dummy-region:dummy-account-number:processing-job/dummy-job-name",
      )
  
      assert isinstance(processing_job, ProcessingJob)
      assert [
          processing_input._to_request_dict()
          for processing_input in processing_job.inputs
      ] == _get_describe_response_inputs_and_ouputs()[
          "ProcessingInputs"
      ]
      assert [
          processing_output._to_request_dict()
          for processing_output in processing_job.outputs
      ] == _get_describe_response_inputs_and_ouputs()[
          "ProcessingOutputConfig"
      ][
          "Outputs"
      ]
      assert (
          processing_job.output_kms_key
          == _get_describe_response_inputs_and_ouputs()[
              "ProcessingOutputConfig"
          ]["KmsKeyId"]
      )
  
imports: from __future__ import absolute_import
  import copy
  import pytest
  from mock import Mock, patch, MagicMock
  from packaging import version
  from sagemaker import LocalSession
  from sagemaker.dataset_definition.inputs import S3Input, DatasetDefinition, AthenaDatasetDefinition, RedshiftDatasetDefinition
  from sagemaker.processing import ProcessingInput, ProcessingOutput, Processor, ScriptProcessor, ProcessingJob
  from sagemaker.session_settings import SessionSettings
  from sagemaker.spark.processing import PySparkProcessor
  from sagemaker.sklearn.processing import SKLearnProcessor
  from sagemaker.pytorch.processing import PyTorchProcessor
  from sagemaker.tensorflow.processing import TensorFlowProcessor
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from sagemaker.xgboost.processing import XGBoostProcessor
  from sagemaker.mxnet.processing import MXNetProcessor
  from sagemaker.network import NetworkConfig
  from sagemaker.processing import FeatureStoreOutput
  from sagemaker.fw_utils import UploadedCode
  from sagemaker.workflow.pipeline_context import PipelineSession, _PipelineConfig
  from sagemaker.workflow.functions import Join
  from sagemaker.workflow.execution_variables import ExecutionVariables
  from tests.unit import SAGEMAKER_CONFIG_PROCESSING_JOB
label_desc: Use image node_id 35 for calling a global function with example usage: test_processing_job_from_processing_arn(sagemaker_session) without return types