code: def generate_assets():
      X_train, y_train, X_test, y_test = titanic_survive()
  
      model = RandomForestClassifier(n_estimators=5, max_depth=2)
      model.fit(X_train, y_train)
  
      explainer = ClassifierExplainer(
          model,
          X_test,
          y_test,
          cats=[
              {"Gender": ["Sex_female", "Sex_male", "Sex_nan"]},
              "Deck",
              "Embarked",
          ],
          labels=["Not survived", "Survived"],
      )
  
      dashboard = ExplainerDashboard(
          explainer,
          [
              ShapDependenceComposite(explainer, title="Test Tab!"),
              ShapDependenceComposite,
              "importances",
          ],
          title="Test Title!",
      )
  
      pkl_dir = Path.cwd() / "tests" / "test_assets"
      explainer.to_yaml(pkl_dir / "explainer.yaml")
      dashboard.to_yaml(
          pkl_dir / "dashboard.yaml",
          explainerfile=str(pkl_dir / "explainer.joblib"),
          dump_explainer=True,
      )
      return None
  
file_path: explainerdashboard/tests/test_cli.py
imports: import pytest
  from pathlib import Path
  from sklearn.ensemble import RandomForestClassifier
  from explainerdashboard import ClassifierExplainer, ExplainerDashboard
  from explainerdashboard.datasets import titanic_survive
  from explainerdashboard.custom import ShapDependenceComposite
label_desc: Use image node_id 1 for calling a global function with example usage: generate_assets() and returns: None