code: def test_cross_validation(self) -> None:
      for autoset_axis_limits in [False, True]:
          cv = cross_validate(self.model)
          # Assert that each type of plot can be constructed successfully
          label_dict = {"branin": "BrAnIn"}
          plot = interact_cross_validation_plotly(
              cv,
              label_dict=label_dict,
              autoset_axis_limits=autoset_axis_limits,
          )
          # pyre-ignore [16]
          x_range = (
              plot.layout.updatemenus[0]
              .buttons[0]
              .args[1]["xaxis.range"]
          )
          y_range = (
              plot.layout.updatemenus[0]
              .buttons[0]
              .args[1]["yaxis.range"]
          )
          if autoset_axis_limits:
              self.assertTrue(
                  (len(x_range) == 2) and (x_range[0] < x_range[1])
              )
              self.assertTrue(
                  (len(y_range) == 2) and (y_range[0] < y_range[1])
              )
          else:
              self.assertIsNone(x_range)
              self.assertIsNone(y_range)
  
          self.assertIsInstance(plot, go.Figure)
          plot = interact_cross_validation(
              cv,
              label_dict=label_dict,
              autoset_axis_limits=autoset_axis_limits,
          )
          self.assertIsInstance(plot, AxPlotConfig)
  
file_path: Ax/ax/plot/tests/test_diagnostic.py
imports: import plotly.graph_objects
  from ax.modelbridge.cross_validation import cross_validate
  from ax.modelbridge.registry import Models
  from ax.plot.base import AxPlotConfig
  from ax.plot.diagnostic import interact_cross_validation, interact_cross_validation_plotly
  from ax.utils.common.testutils import TestCase
  from ax.utils.testing.core_stubs import get_branin_experiment
  from ax.utils.testing.mock import fast_botorch_optimize
label_desc: Use image node_id 2 for calling the DiagnosticTest obj's underlying member method code with example usage: obj.test_cross_validation() without return types