code: def test_partial_dependence_plots__validate_and_normalize_pdp_args__none_args(
      col_number_warning,
  ):
      train_data = pd.read_csv(
          os.path.join(RESOURCE_PATH, "adult", "train_data.csv")
      )
      chart_args, fig_args, features = _validate_and_normalize_pdp_args(
          train_data,
          features=None,
          fig_args=None,
          chart_args=None,
          col_number_warning=col_number_warning,
      )
      assert chart_args == {}
      assert fig_args == {}
      assert features is None
  
imports: import os
  import re
  import tempfile
  from sys import platform
  from unittest.mock import ANY, MagicMock, call
  import numpy
  import pandas
  import pytest
  import autogluon.eda
  from autogluon.eda import AnalysisState
  from autogluon.eda.analysis import AnomalyDetectorAnalysis, Namespace, ShapAnalysis
  from autogluon.eda.analysis.base import BaseAnalysis
  from autogluon.eda.auto import analyze, analyze_interaction, covariate_shift_detection, dataset_overview, detect_anomalies, explain_rows, partial_dependence_plots, quick_fit, target_analysis
  from autogluon.eda.auto.simple import _is_single_numeric_variable, _prepare_pdp_data, _validate_and_normalize_pdp_args, get_default_estimator_if_not_specified, get_empty_dict_if_none
  from autogluon.eda.visualization import AnomalyScoresVisualization, ConfusionMatrix, CorrelationVisualization, DatasetStatistics, DatasetTypeMismatch, ExplainForcePlot, ExplainWaterfallPlot, FeatureImportance, FeatureInteractionVisualization, LabelInsightsVisualization, MarkdownSectionComponent, ModelLeaderboard, PropertyRendererComponent, RegressionEvaluation, XShiftSummary
  from autogluon.eda.visualization.base import AbstractVisualization
  from autogluon.eda.visualization.interaction import FeatureDistanceAnalysisVisualization, PDPInteractions
label_desc: Use image node_id 20 for calling a global function with example usage: test_partial_dependence_plots__validate_and_normalize_pdp_args__none_args(col_number_warning) without return types