code: def test_multi_ax_input(sample_metric_frame):
      """Tests plotting function works with multiple axis input."""
      fig, ax = plt.subplots(nrows=1, ncols=2)
      ax[0].set_title("Recall Plot")
      ax[0].set_ylabel("Recall")
      ax[0].set_xlabel("Race")
      ax[0].set_ylim((0, 1))
      ax = plot_metric_frame(
          sample_metric_frame,
          metrics=["Recall", "Accuracy"],
          conf_intervals=["Recall Bounds", "Accuracy Bounds"],
          ax=ax,
          kind="bar",
          colormap="Pastel1",
      )
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import pytest
  from sklearn.metrics import accuracy_score, confusion_matrix, recall_score
  from sklearn.utils import check_consistent_length
  from fairlearn.experimental.enable_metric_frame_plotting import plot_metric_frame
  from fairlearn.metrics import MetricFrame
  from fairlearn.metrics._plotter import _CONF_INTERVALS_FLIPPED_BOUNDS_ERROR, _CONF_INTERVALS_MUST_BE_ARRAY, _METRIC_FRAME_INVALID_ERROR
  from .data_for_test import g_1, y_p, y_t
label_desc: Use image node_id 12 for calling a global function with example usage: test_multi_ax_input(sample_metric_frame) without return types