code: def _classification_report_add(first, second, keys, target_names, ax):
      _matrix.add(first, second, ax, invert_axis=True, max_=1.0)
  
      ax.set_xticks(range(len(keys)))
      ax.set_xticklabels(keys)
  
      tick_marks = np.arange(len(target_names))
      ax.set_yticks(tick_marks)
      ax.set_yticklabels(target_names)
  
      ax.set(
          title="Classification report (compare)",
          xlabel="Metric",
          ylabel="Class",
      )
  
imports: from warnings import warn
  from pathlib import Path
  import json
  import numpy
  import matplotlib.pyplot
  from sklearn.metrics import classification_report
  from ..telemetry import SKLearnEvaluationLogger
  from sklearn_evaluation.plot.classification import _add_values_to_matrix
  from sklearn_evaluation.util import default_heatmap
  from sklearn_evaluation.plot.plot import Plot
  from sklearn_evaluation.plot import _matrix
  from sklearn_evaluation import __version__
  from ploomber_core.exceptions import modify_exceptions
label_desc: Use image node_id 1 for calling a global function with example usage: _classification_report_add(first, second, keys, target_names, ax) without return types