code: def test_run_on_s3_analysis_config_file(
      processor_run, sagemaker_session, clarify_processor, data_config
  ):
      analysis_config = {
          "dataset_type": "text/csv",
          "methods": {"post_training_bias": {"methods": "all"}},
      }
      with patch(
          "sagemaker.clarify._upload_analysis_config", return_value=None
      ) as mock_method:
          clarify_processor._run(
              data_config,
              analysis_config,
              True,
              True,
              "test",
              None,
              {"ExperimentName": "AnExperiment"},
          )
          analysis_config_file = mock_method.call_args[0][0]
          mock_method.assert_called_with(
              analysis_config_file,
              data_config.s3_output_path,
              sagemaker_session,
              None,
          )
  
          data_config_with_analysis_config_output = DataConfig(
              s3_data_input_path="s3://input/train.csv",
              s3_output_path="s3://output/analysis_test_result",
              s3_analysis_config_output_path="s3://analysis_config_output",
              label="Label",
              headers=[
                  "Label",
                  "F1",
                  "F2",
                  "F3",
              ],
              dataset_type="text/csv",
          )
          clarify_processor._run(
              data_config_with_analysis_config_output,
              analysis_config,
              True,
              True,
              "test",
              None,
              {"ExperimentName": "AnExperiment"},
          )
          analysis_config_file = mock_method.call_args[0][0]
          mock_method.assert_called_with(
              analysis_config_file,
              data_config_with_analysis_config_output.s3_analysis_config_output_path,
              sagemaker_session,
              None,
          )
  
imports: from __future__ import absolute_import, print_function
  import copy
  import pytest
  from mock import MagicMock, Mock, patch
  from sagemaker import Processor, image_uris
  from sagemaker.clarify import BiasConfig, DataConfig, ModelConfig, ModelPredictedLabelConfig, PDPConfig, SageMakerClarifyProcessor, SHAPConfig, TextConfig, ImageConfig, _AnalysisConfigGenerator, DatasetType, ProcessingOutputHandler, SegmentationConfig
label_desc: Use image node_id 39 for calling a global function with example usage: test_run_on_s3_analysis_config_file(processor_run, sagemaker_session, clarify_processor, data_config) without return types