code: def test_analysis_config_generator_for_bias_pre_training(
      data_config, data_bias_config
  ):
      actual = _AnalysisConfigGenerator.bias_pre_training(
          data_config, data_bias_config, methods="all"
      )
      expected = {
          "dataset_type": "text/csv",
          "facet": [{"name_or_index": "F1"}],
          "group_variable": "F2",
          "headers": ["Label", "F1", "F2", "F3", "F4"],
          "joinsource_name_or_index": "F4",
          "label": "Label",
          "label_values_or_threshold": [1],
          "methods": {
              "report": {"name": "report", "title": "Analysis Report"},
              "pre_training_bias": {"methods": "all"},
          },
      }
      assert actual == expected
  
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 52 for calling a global function with example usage: test_analysis_config_generator_for_bias_pre_training(data_config, data_bias_config) without return types