code: def _get_contour_plot(info: _ContourInfo) -> "Axes":
      sorted_params = info.sorted_params
      sub_plot_infos = info.sub_plot_infos
      reverse_scale = info.reverse_scale
      target_name = info.target_name
  
      if len(sorted_params) <= 1:
          _, ax = plt.subplots()
          return ax
      n_params = len(sorted_params)
  
      plt.style.use(
          "ggplot"
      )  # Use ggplot style sheet for similar outputs to plotly.
      if n_params == 2:
          # Set up the graph style.
          fig, axs = plt.subplots()
          axs.set_title("Contour Plot")
          cmap = _set_cmap(reverse_scale)
  
          cs = _generate_contour_subplot(
              sub_plot_infos[0][0], axs, cmap
          )
          if isinstance(cs, ContourSet):
              axcb = fig.colorbar(cs)
              axcb.set_label(target_name)
      else:
          # Set up the graph style.
          fig, axs = plt.subplots(n_params, n_params)
          fig.suptitle("Contour Plot")
          cmap = _set_cmap(reverse_scale)
  
          # Prepare data and draw contour plots.
          cs_list = []
          for x_i in range(len(sorted_params)):
              for y_i in range(len(sorted_params)):
                  ax = axs[y_i, x_i]
                  cs = _generate_contour_subplot(
                      sub_plot_infos[y_i][x_i], ax, cmap
                  )
                  if isinstance(cs, ContourSet):
                      cs_list.append(cs)
          if cs_list:
              axcb = fig.colorbar(cs_list[0], ax=axs)
              axcb.set_label(target_name)
  
      return axs
  
imports: from __future__ import annotations
  from typing import Callable
  from typing import Sequence
  import numpy
  from optuna._experimental import experimental_func
  from optuna._imports import try_import
  from optuna.logging import get_logger
  from optuna.study import Study
  from optuna.trial import FrozenTrial
  from optuna.visualization._contour import _AxisInfo
  from optuna.visualization._contour import _ContourInfo
  from optuna.visualization._contour import _get_contour_info
  from optuna.visualization._contour import _PlotValues
  from optuna.visualization._contour import _SubContourInfo
  from optuna.visualization.matplotlib._matplotlib_imports import _imports
label_desc: Use image node_id 2 for calling a global function with example usage: _get_contour_plot(info) and returns: axs, ax